A well-prepared abstract enables the reader to identify the basic content of a document quickly and accurately, to determine its relevance to their interests, and thus to decide whether to read the document in its entirety. The Abstract should be informative and completely self-explanatory, provide a clear statement of the problem, the proposed approach or solution, and point out major findings and conclusions. The Abstract should be 100 to 150 words in length. The abstract should be written in the past tense. Standard nomenclature should be used and abbreviations should be avoided. No literature should be cited. The keyword list provides the opportunity to add keywords, used by the indexing and abstracting services, in addition to those already present in the title. Judicious use of keywords may increase the ease with which interested parties can locate our article.
Filter technique of medical image on multiple morphological gradient methodTELKOMNIKA JOURNAL
Filter technique is supportive for reducing image noise. This paper presents a study on filtering medical images, i.e., CT-Scan, Chest X-ray and Panoramic X-ray collected from two of the most prominent public hospitals in Padang City, Indonesia. The aim of this study preserved to facilitate in diagnosing objects in x-ray medical images. This study used filter technique, i.e. Blur, Emboss, Gaussian, Laplacian, Roberts, Sharpen, or Sobel techniques as pre-processing step. The filter process performed before edge detection and edge clarification. MMG method used in this study to clarify the edge detection. Thus, this research showed the hesitation decline (confidence increase) of the diagnosis of objects contained in medical images.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image Enhancement using Guided Filter for under Exposed ImagesDr. Amarjeet Singh
Image enhancement becomes an important step to
improve the quality of image and change in the appearance of
the image in such a way that either a human or a machine can
fetch certain information from the image after a change. Due
to low contrast images it becomes very difficult to get any
information out of it. In today’s digital world of imaging
image enhancement is a very useful in various applications
ranging from electronics printing to recognition. For highly
underexposed region, intensity bin are present in darken
region that’s by such images lacks in saturation and suffers
from low intensity. Power law transformation provides
solution to this problem. It enhances the brightness so as
image at least becomes visible. To modify the intensity level
histogram equalization can be used. In this we can apply
cumulative density function and probabilistic density function
so as to divide the image into sub images.
In proposed approach to provide betterment in
results guided filter has been applied to images after
equalization so that we can get better Entropy rate and
Coefficient of correlation can be improved with previously
available techniques. The guided filter is derived from local
linear model. The guided filter computes the filtering output
by considering the content of guidance image, which can be
the image itself or other targeted image.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Adaptive K-Means Clustering Algorithm for MR Breast Image Segmentation
3D Brain Tumor Segmentation Scheme using K-mean Clustering and Connected Component Labeling Algorithms
Volume Identification and Estimation of MRI Brain Tumor
MRI Breast cancer diagnosis hybrid approach using adaptive Ant-based segmentation and Multilayer Perceptron NN classifier
Filter technique of medical image on multiple morphological gradient methodTELKOMNIKA JOURNAL
Filter technique is supportive for reducing image noise. This paper presents a study on filtering medical images, i.e., CT-Scan, Chest X-ray and Panoramic X-ray collected from two of the most prominent public hospitals in Padang City, Indonesia. The aim of this study preserved to facilitate in diagnosing objects in x-ray medical images. This study used filter technique, i.e. Blur, Emboss, Gaussian, Laplacian, Roberts, Sharpen, or Sobel techniques as pre-processing step. The filter process performed before edge detection and edge clarification. MMG method used in this study to clarify the edge detection. Thus, this research showed the hesitation decline (confidence increase) of the diagnosis of objects contained in medical images.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image Enhancement using Guided Filter for under Exposed ImagesDr. Amarjeet Singh
Image enhancement becomes an important step to
improve the quality of image and change in the appearance of
the image in such a way that either a human or a machine can
fetch certain information from the image after a change. Due
to low contrast images it becomes very difficult to get any
information out of it. In today’s digital world of imaging
image enhancement is a very useful in various applications
ranging from electronics printing to recognition. For highly
underexposed region, intensity bin are present in darken
region that’s by such images lacks in saturation and suffers
from low intensity. Power law transformation provides
solution to this problem. It enhances the brightness so as
image at least becomes visible. To modify the intensity level
histogram equalization can be used. In this we can apply
cumulative density function and probabilistic density function
so as to divide the image into sub images.
In proposed approach to provide betterment in
results guided filter has been applied to images after
equalization so that we can get better Entropy rate and
Coefficient of correlation can be improved with previously
available techniques. The guided filter is derived from local
linear model. The guided filter computes the filtering output
by considering the content of guidance image, which can be
the image itself or other targeted image.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Adaptive K-Means Clustering Algorithm for MR Breast Image Segmentation
3D Brain Tumor Segmentation Scheme using K-mean Clustering and Connected Component Labeling Algorithms
Volume Identification and Estimation of MRI Brain Tumor
MRI Breast cancer diagnosis hybrid approach using adaptive Ant-based segmentation and Multilayer Perceptron NN classifier
The Performance Analysis of Median Filter for Suppressing Impulse Noise from ...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Medical Image Fusion Using Discrete Wavelet TransformIJERA Editor
Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multimodal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. The domain where image fusion is readily used nowadays is in medical diagnostics to fuse medical images such as CT (Computed Tomography), MRI (Magnetic Resonance Imaging) and MRA. This paper aims to present a new algorithm to improve the quality of multimodality medical image fusion using Discrete Wavelet Transform (DWT) approach. Discrete Wavelet transform has been implemented using different fusion techniques including pixel averaging, maximum minimum and minimum maximum methods for medical image fusion. Performance of fusion is calculated on the basis of PSNR, MSE and the total processing time and the results demonstrate the effectiveness of fusion scheme based on wavelet transform.
A new methodology for sp noise removal in digital image processing ijfcstjournal
The paper purposes the removal of noise in digital gray scale images that often observed in scanned
documents. Generally, Data i.e. picture, text can be contaminated by an additive noise during the process
of scanning. This methodology prevents this type of noise known as Salt and Pepper noise (SP Noise) which
causes white and black spots on the original image. We are designing a new algorithm for removal of these
white and black spots after the knowledge of Median Filter, Adaptive Filter and the new proposed
algorithm will definitely protect the image from noise and distortion. Firstly, Adaptive Histogram
Equalization is done on the original image. Secondly apply Adaptive contrast Enhancement Technique on
the resultant image. After Contrast Enhancement we apply filters Such as Homomorphic filtering. These
filters are applied sequentially on distorted images for removing the image.
Contrast enhancement of color images using improved retinex methodeSAT Journals
Abstract Color images provide large information for human visual perception compared to grayscale images. Color image enhancement methods enhance the visual data to increase the clarity of the color image. It increases human perception of information. Different color image contrast enhancement methods are used to increase the contrast of the color images. The Retinex algorithms enhance the color images similar to the scene perceived by the human eye. Multiscale retinex with color restoration (MSRCR) is a type of retinex algorithm. The MSRCR algorithm results in graying out and halo artifacts at the edges of the images. So here the focus is on improving the MSRCR algorithm by combining it with contrast limited adaptive histogram equalization (CLAHE) using image. Keywords: color image enhancement,retinex algorithms
A Novel Adaptive Denoising Method for Removal of Impulse Noise in Images usin...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Brain Tumor Area Calculation in CT-scan image using Morphological Operationsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
41 9147 quantization encoding algorithm based edit tyasIAESIJEECS
In the field of digital data there is a demand in bandwidth for the transmission of the videos and images all over the worlds. So in order to reduce the storage space in the field of image applications there is need for the image compression process with lesser transmission bandwidth. So in this paper we are proposing a new image compression technique for the compression of the satellite images by using the Region of Interest (ROI) based on the lossy image technique called the Quantization encoding algorithm for the compression. The performance of our method can be evaluated and analyzing the PSNR values of the output images.
Ultrasound medical images are very important component of the diagnostics process.
As a part of image analysis, edge detection is often considered for further segmentation
or more precise measurements of patterns in the picture. Unfortunately, ultrasound
images are subject to degradations, especially speckle noise which is also a high
frequency component. Conventional edge detector can detect edges in image with additive
noise effectively but not ultrasound image that are corrupted by multiplicative speckle
noise which alleviates image resolution resulting in inaccurate characterization of object
features. In this paper, anisotropic diffusion and PSO-EM based edge detectors are
analyzed and compared for the suppression of the multiplicative noise effectively while
preserving the edge of the object in ultrasound image. The result shows that the proposed
methods provided better result than conventional method
Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filterijtsrd
In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise salt and pepper noise . The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter SMF , Decision Based Median Filter DBMF and Modified Decision Based Median Filter MDBMF etc. The main objective of the proposed method was to improve peak signal to noise ratio PSNR , visual perception and reduction in blurring of image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0's and 255's are present in the particular window and all the pixel values are 0's and 255's then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via proposed method. The experimental result shows better peak signal to noise ratio PSNR , mean square error MSE and mean absolute error MAE values with better visual and human perception. Sonali Malviya | Prof. Anshuj Jain "Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19086.pdf
http://www.ijtsrd.com/engineering/computer-engineering/19086/analysis-psnr-of-high-density-salt-and-pepper-impulse-noise-using-median-filter/sonali-malviya
Efficient Brain Tumor Detection Using Wavelet TransformIJERA Editor
Brain tumor detection is a challenging task and its very important to analyze the structure of the tumor correctly so a automatic method is used now a days for the detection of the tumor. This method saves time as well as it reduces the error which occurs in the method of manual detection. In this paper the tumor is detected using wavelet transform. MRI is an important tool used in many fields of medicine and is capable of generating a detailed image of any part of the human body. The tumor is segmented from the MRI images, features are extracted and then the area of the tumor is determined. PNN can successfully handle the process of brain tumor classification
An Efficient Image Denoising Approach for the Recovery of Impulse NoisejournalBEEI
Image noise is one of the key issues in image processing applications today. The noise will affect the quality of the image and thus degrades the actual information of the image. Visual quality is the prerequisite for many imagery applications such as remote sensing. In recent years, the significance of noise assessment and the recovery of noisy images are increasing. The impulse noise is characterized by replacing a portion of an image’s pixel values with random values Such noise can be introduced due to transmission errors. Accordingly, this paper focuses on the effect of visual quality of the image due to impulse noise during the transmission of images. In this paper, a hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images. We further proved the performance of the proposed image enhancement scheme using the advanced performance metrics.
Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentatio...IJECEIAES
Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.
Correction of Inhomogeneous MR Images Using Multiscale RetinexCSCJournals
A new method for enhancing the contrast of magnetic resonance images (MRI) by retinex algorithm is proposed. It can correct the blurrings in deep anatomical structures and inhomogeneity of MRI. Multiscale retinex (MSR) employed SSR with different weightings to correct inhomogeneities and enhance the contrast of MR images. The method was assessed by applying it to phantom and animal images acquired on MRI scanner systems. Its performance was also compared with other methods based on two indices: (1) the peak signal-to-noise ratio (PSNR) and (2) the contrast-to-noise ratio (CNR). Two indices, including PSNR and CNR, were used to evaluate the performance of correction of inhomogeneity in MR images. The PSNR/CNR of a phantom and animal images were 11.8648 dB/2.0922 and 11.7580 dB/2.1157, respectively, which were higher or very close to the results of wavelet algorithm. The retinex algorithm successfully corrected a nonuniform grayscale, enhanced contrast, corrected inhomogeneity, and clarified the deep brain structures of MR images captured by surface coils and outperformed histogram equalization, local histogram equalization, and a waveletbased algorithm, and hence may be a valuable method in MR image processing.
Image De-noising and Enhancement for Salt and Pepper Noise using Genetic Algo...IDES Editor
Image Enhancement through De-noising is one of
the most important applications of Digital Image Processing
and is still a challenging problem. Images are often received
in defective conditions due to usage of Poor image sensors,
poor data acquisition process and transmission errors etc.,
which creates problems for the subsequent process to
understand such images. The proposed Genetic filter is capable
of removing noise while preserving the fine details, as well as
structural image content. It can be divided into: (i) de-noising
filtering, and (ii) enhancement filtering. Image Denoising
and enhancement are essential part of any image processing
system, whether the processed information is utilized for visual
interpretation or for automatic analysis. The Experimental
results performed on a set of standard test images for a wide
range of noise corruption levels shows that the proposed filter
outperforms standard procedures for salt and pepper removal
both visually and in terms of performance measures such as
PSNR.Genetic algorithms will definitely helpful in solving
various complex image processing tasks in the future.
In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated noise percentages. For image quality measurement, two performance measuring indices are used: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The simulation results show that the performance of some specific filters in reducing some types of noise are much better than others. It has been illustrated that median filter is more appropriate for eliminating salt and pepper noise. Averaging filter still works well for such type of noise, but of less performance quality than the median filter. Gaussian and Wiener filters outperform other filters in restoring mages corrupted with Poisson and speckle noise.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The Performance Analysis of Median Filter for Suppressing Impulse Noise from ...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Medical Image Fusion Using Discrete Wavelet TransformIJERA Editor
Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multimodal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. The domain where image fusion is readily used nowadays is in medical diagnostics to fuse medical images such as CT (Computed Tomography), MRI (Magnetic Resonance Imaging) and MRA. This paper aims to present a new algorithm to improve the quality of multimodality medical image fusion using Discrete Wavelet Transform (DWT) approach. Discrete Wavelet transform has been implemented using different fusion techniques including pixel averaging, maximum minimum and minimum maximum methods for medical image fusion. Performance of fusion is calculated on the basis of PSNR, MSE and the total processing time and the results demonstrate the effectiveness of fusion scheme based on wavelet transform.
A new methodology for sp noise removal in digital image processing ijfcstjournal
The paper purposes the removal of noise in digital gray scale images that often observed in scanned
documents. Generally, Data i.e. picture, text can be contaminated by an additive noise during the process
of scanning. This methodology prevents this type of noise known as Salt and Pepper noise (SP Noise) which
causes white and black spots on the original image. We are designing a new algorithm for removal of these
white and black spots after the knowledge of Median Filter, Adaptive Filter and the new proposed
algorithm will definitely protect the image from noise and distortion. Firstly, Adaptive Histogram
Equalization is done on the original image. Secondly apply Adaptive contrast Enhancement Technique on
the resultant image. After Contrast Enhancement we apply filters Such as Homomorphic filtering. These
filters are applied sequentially on distorted images for removing the image.
Contrast enhancement of color images using improved retinex methodeSAT Journals
Abstract Color images provide large information for human visual perception compared to grayscale images. Color image enhancement methods enhance the visual data to increase the clarity of the color image. It increases human perception of information. Different color image contrast enhancement methods are used to increase the contrast of the color images. The Retinex algorithms enhance the color images similar to the scene perceived by the human eye. Multiscale retinex with color restoration (MSRCR) is a type of retinex algorithm. The MSRCR algorithm results in graying out and halo artifacts at the edges of the images. So here the focus is on improving the MSRCR algorithm by combining it with contrast limited adaptive histogram equalization (CLAHE) using image. Keywords: color image enhancement,retinex algorithms
A Novel Adaptive Denoising Method for Removal of Impulse Noise in Images usin...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Brain Tumor Area Calculation in CT-scan image using Morphological Operationsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
41 9147 quantization encoding algorithm based edit tyasIAESIJEECS
In the field of digital data there is a demand in bandwidth for the transmission of the videos and images all over the worlds. So in order to reduce the storage space in the field of image applications there is need for the image compression process with lesser transmission bandwidth. So in this paper we are proposing a new image compression technique for the compression of the satellite images by using the Region of Interest (ROI) based on the lossy image technique called the Quantization encoding algorithm for the compression. The performance of our method can be evaluated and analyzing the PSNR values of the output images.
Ultrasound medical images are very important component of the diagnostics process.
As a part of image analysis, edge detection is often considered for further segmentation
or more precise measurements of patterns in the picture. Unfortunately, ultrasound
images are subject to degradations, especially speckle noise which is also a high
frequency component. Conventional edge detector can detect edges in image with additive
noise effectively but not ultrasound image that are corrupted by multiplicative speckle
noise which alleviates image resolution resulting in inaccurate characterization of object
features. In this paper, anisotropic diffusion and PSO-EM based edge detectors are
analyzed and compared for the suppression of the multiplicative noise effectively while
preserving the edge of the object in ultrasound image. The result shows that the proposed
methods provided better result than conventional method
Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filterijtsrd
In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise salt and pepper noise . The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter SMF , Decision Based Median Filter DBMF and Modified Decision Based Median Filter MDBMF etc. The main objective of the proposed method was to improve peak signal to noise ratio PSNR , visual perception and reduction in blurring of image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0's and 255's are present in the particular window and all the pixel values are 0's and 255's then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via proposed method. The experimental result shows better peak signal to noise ratio PSNR , mean square error MSE and mean absolute error MAE values with better visual and human perception. Sonali Malviya | Prof. Anshuj Jain "Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19086.pdf
http://www.ijtsrd.com/engineering/computer-engineering/19086/analysis-psnr-of-high-density-salt-and-pepper-impulse-noise-using-median-filter/sonali-malviya
Efficient Brain Tumor Detection Using Wavelet TransformIJERA Editor
Brain tumor detection is a challenging task and its very important to analyze the structure of the tumor correctly so a automatic method is used now a days for the detection of the tumor. This method saves time as well as it reduces the error which occurs in the method of manual detection. In this paper the tumor is detected using wavelet transform. MRI is an important tool used in many fields of medicine and is capable of generating a detailed image of any part of the human body. The tumor is segmented from the MRI images, features are extracted and then the area of the tumor is determined. PNN can successfully handle the process of brain tumor classification
An Efficient Image Denoising Approach for the Recovery of Impulse NoisejournalBEEI
Image noise is one of the key issues in image processing applications today. The noise will affect the quality of the image and thus degrades the actual information of the image. Visual quality is the prerequisite for many imagery applications such as remote sensing. In recent years, the significance of noise assessment and the recovery of noisy images are increasing. The impulse noise is characterized by replacing a portion of an image’s pixel values with random values Such noise can be introduced due to transmission errors. Accordingly, this paper focuses on the effect of visual quality of the image due to impulse noise during the transmission of images. In this paper, a hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images. We further proved the performance of the proposed image enhancement scheme using the advanced performance metrics.
Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentatio...IJECEIAES
Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.
Correction of Inhomogeneous MR Images Using Multiscale RetinexCSCJournals
A new method for enhancing the contrast of magnetic resonance images (MRI) by retinex algorithm is proposed. It can correct the blurrings in deep anatomical structures and inhomogeneity of MRI. Multiscale retinex (MSR) employed SSR with different weightings to correct inhomogeneities and enhance the contrast of MR images. The method was assessed by applying it to phantom and animal images acquired on MRI scanner systems. Its performance was also compared with other methods based on two indices: (1) the peak signal-to-noise ratio (PSNR) and (2) the contrast-to-noise ratio (CNR). Two indices, including PSNR and CNR, were used to evaluate the performance of correction of inhomogeneity in MR images. The PSNR/CNR of a phantom and animal images were 11.8648 dB/2.0922 and 11.7580 dB/2.1157, respectively, which were higher or very close to the results of wavelet algorithm. The retinex algorithm successfully corrected a nonuniform grayscale, enhanced contrast, corrected inhomogeneity, and clarified the deep brain structures of MR images captured by surface coils and outperformed histogram equalization, local histogram equalization, and a waveletbased algorithm, and hence may be a valuable method in MR image processing.
Image De-noising and Enhancement for Salt and Pepper Noise using Genetic Algo...IDES Editor
Image Enhancement through De-noising is one of
the most important applications of Digital Image Processing
and is still a challenging problem. Images are often received
in defective conditions due to usage of Poor image sensors,
poor data acquisition process and transmission errors etc.,
which creates problems for the subsequent process to
understand such images. The proposed Genetic filter is capable
of removing noise while preserving the fine details, as well as
structural image content. It can be divided into: (i) de-noising
filtering, and (ii) enhancement filtering. Image Denoising
and enhancement are essential part of any image processing
system, whether the processed information is utilized for visual
interpretation or for automatic analysis. The Experimental
results performed on a set of standard test images for a wide
range of noise corruption levels shows that the proposed filter
outperforms standard procedures for salt and pepper removal
both visually and in terms of performance measures such as
PSNR.Genetic algorithms will definitely helpful in solving
various complex image processing tasks in the future.
In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated noise percentages. For image quality measurement, two performance measuring indices are used: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The simulation results show that the performance of some specific filters in reducing some types of noise are much better than others. It has been illustrated that median filter is more appropriate for eliminating salt and pepper noise. Averaging filter still works well for such type of noise, but of less performance quality than the median filter. Gaussian and Wiener filters outperform other filters in restoring mages corrupted with Poisson and speckle noise.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A statistical approach on pulmonary tuberculosis detection system based on X-...TELKOMNIKA JOURNAL
This paper presented the research result on the design of pulmonary TB (Tuberculosis) detection systems using a statistical approach. The study aimed to address two problems in detecting pulmonary TB by doctors, especially in remote areas of Indonesia, namely the long waiting time for patients to get the doctor's diagnosis and the doctor's subjectivity. We used hundreds of X-ray images from radiology department of Sardjito Hospital, Yogyakarta, as primary data and thirty data from various sources on the internet as secondary data. Using statistical approach, we exploited statistical image feature from image histogram, examined two statistical methods of PCA and LDA transformation for feature extraction, and two minimum distance classifier in image classification. We also used histogram equalization in the image enhancement process and bicubic interpolation in image segmentation and template making. Test results on primary and secondary data images show the identification accuracy of 94% and 83.3%, respectively.
Enhancement of Medical Images using Histogram Based Hybrid TechniqueINFOGAIN PUBLICATION
Digital Image Processing is very important area of research. A number of techniques are available for image enhancement of gray scale images as well as color images. They work very efficiently for enhancement of the gray scale as well as color images. Important techniques namely Histogram Equalization, BBHE, RSWHE, RSWHE (recursion=2, gamma=No), AGCWD (Recursion=0, gamma=0) have been used quite frequently for image enhancement. But there are some shortcomings of the present techniques. The major shortcoming is that while enhancement, the brightness of the image deteriorates quite a lot. So there was need for some technique for image enhancement so that while enhancement was done, the brightness of the images does not go down. To remove this shortcoming, a new hybrid technique namely RESWHE+AGCWD (recursion=2, gamma=0 or 1) was proposed. The results of the proposed technique were compared with the existing techniques. In the present methodology, the brightness did not decrease during image enhancement. So the results and the technique was validated and accepted. The parameters via PSNR, MSE, AMBE etc. are taken for performance evaluation and validation of the proposed technique against the existing techniques which results in better outperform.
OFCS: Optimized Framework of Compressive Sensing for Medical Images in Bottle...IJECEIAES
Compressive sensing is one of teh cost effective solution towards performing compression of heavier form of signals. We reviewed the existing research contribution towards compressive sensing to find that existing system doesnt offer any form of optimization for which reason the signal are superiorly compressed but at the cost of enough resources. Therefore, we introduce a framework that optimizes the performance of the compressive sensing by introducing 4 sequential algorithms for performing Random Sampling, Lossless Compression for region-of-interest, Compressive Sensing using transform-based scheme, and optimization. The contribution of proposed paper is a good balance between computational efficiency and quality of reconstructed medical image when transmitted over network with low channel capacity. The study outcome shows that proposed system offers maximum signal quality and lower algorithm processing time in contrast to existing compression techniuqes on medical images.
INVESTIGATION THE EFFECT OF USING GRAY LEVEL AND RGB CHANNELS ON BRAIN TUMOR ...csandit
Analysis the effect of using gray level on the Brain tumor image for improving speed of object
detection in the field of Medical Image using image processing technique. Specific areas of
interest are image binarization method, Image segmentation. Experiments will be performed by
image processing using Matlab. This paper presents a strategy for decreasing the calculation
time by using gray level and just one channel Red or Green or Blue in medical Image and
analysis its impact in order to improve detection time and the main goal is to reduce time
complexity.
BFO – AIS: A Framework for Medical Image Classification Using Soft Computing ...ijsc
Medical images provide diagnostic evidence/information about anatomical pathology. The growth in database is enormous as medical digital image equipment’s like Magnetic Resonance Images (MRI), Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work. CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio therapy. Medical information systems goals are to deliver information to right persons at the right time and place to improve care process quality and efficiency. This paper proposes an Artificial Immune System (AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO) with Local Search (LS) for medical image classification.
BFO – AIS: A FRAME WORK FOR MEDICAL IMAGE CLASSIFICATION USING SOFT COMPUTING...ijsc
Medical images provide diagnostic evidence/information about anatomical pathology. The growth in
database is enormous as medical digital image equipment’s like Magnetic Resonance Images (MRI),
Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work.
CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more
reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio
therapy. Medical information systems goals are to deliver information to right persons at the right time and
place to improve care process quality and efficiency. This paper proposes an Artificial Immune System
(AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO)
with Local Search (LS) for medical image classification.
Computer Aided Diagnosis using Margin and Posterior Acoustic Featuresfor Brea...TELKOMNIKA JOURNAL
Breast cancer is the most commonly diagnosed cancer among females worldwide. Computer aided diagnosis (CAD) was developed to assist radiologists in detecting and evaluating nodules so it can improve diagnostic accuracy, avoid unnecessary biopsies, reduce anxiety and control costs. This research proposes a method of CAD for breast ultrasound images based on margin and posterior acoustic features. It consists of preprocessing, segmentation using active contour without edge (ACWE) and morphological, feature extraction and classification. Texture and geometry analysis was used to determine the characteristics of the posterior acoustic and margin nodules. Support vector machines (SVM) provided better performance than multilayer perceptron (MLP). The performance of proposed method achieved the accuracy of 91.35%, sensitivity of 92.00%, specificity of 89.66%, PPV of 95.83%, NPV of 81.26% and Kappa of 0.7915. These results indicate that the developed CAD has potential to be implemented for diagnosis of breast cancer using ultrasound images.
An approach for cross-modality guided quality enhancement of liver imageIJECEIAES
A novel approach for multimodal liver image contrast enhancement is put forward in this paper. The proposed approach utilizes magnetic resonance imaging (MRI) scan of liver as a guide to enhance the structures of computed tomography (CT) liver. The enhancement process consists of two phases: The first phase is the transformation of MRI and CT modalities to be in the same range. Then the histogram of CT liver is adjusted to match the histogram of MRI. In the second phase, an adaptive histogram equalization technique is presented by splitting the CT histogram into two sub-histograms and replacing their cumulative distribution functions with two smooths sigmoid. The subjective and objective assessments of experimental results indicated that the proposed approach yields better results. In addition, the image contrast is effectively enhanced as well as the mean brightness and details are well preserved.
Image Segmentation Based Survey on the Lung Cancer MRI ImagesIIRindia
Educational data mining (EDM) creates high impact in the field of academic domain. The methods used in this topic are playing a major advanced key role in increasing knowledge among students. EDM explores and gives ideas in understanding behavioral patterns of students to choose a correct path for choosing their carrier. This survey focuses on such category and it discusses on various techniques involved in making educational data mining for their knowledge improvement. Also, it discusses about different types of EDM tools and techniques in this article. Among the different tools and techniques, best categories are suggested for real world usage.
In general, mammogram images are contaminated with noise which directly affects image quality. Several methods have been proposed to de-noise these images, however, there is always a risk of losing valuable information. In order to overcome the loss of information, the present study proposed a Hybrid denoising method for mammogram images. The proposed hybrid method works in two steps: Firstly, preprocessing with mathematical morphology was applied for image enhancement. Secondly, a global unsymmetrical trimmed median filter (GUTM) is applied to a de-noise image. Experimental results prove that the proposed method works well for mammogram images. Hence, the study provided an alternative method for denoising mammogram images.
An image enhancement method based on gabor filtering in wavelet domain and ad...nooriasukmaningtyas
The images are not always good enough to convey the proper information.
The image may be very bright or very dark sometime or it may be low
contrast or high contrast. Because of these reasons image enhancement plays
important role in digital image processing. In this paper we proposed an
image enhancement technique in which gabor and median filtering is
performed in wavelet domain and adaptive histogram equalization is
performed in spatial domain. Brightness and contrast are the two parameters
Keywords: used for analyzing the performance of the proposed method.
Similar to Histogram Equalization for Improving Quality of Low-Resolution Ultrasonography Images (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
2. ISSN: 1693-6930
TELKOMNIKA Vol. 15, No. 3, September 2017: 1397 – 1408
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The proposed models were tested vigorously using various test images obtained and
the experimental results proved that the proposed models produce significant improvement over
the existing traditional systems. Lalotra [8] discussed about quality of fused image can be
enhanced by using combination of Butterworth High Pass filter and Cross Bilateral filter. Vaezi
[9] proposed a novel and effective semi-automatic method to improve the quality of 2D image
segmentation process. Kumar [10] discussed about a novel, structured visual quality
improvement mechanism based on daubechies (db) wavelet transform. In the proposed
methodology, the segmentation of the ultrasound medical image is carried out with the help of
active contour technique. Nagata [11] evaluated the radiation dose and image quality comparing
low-dose CT colonography (CTC) reconstructed using different levels of iterative reconstruction
techniques with routine-dose CTC reconstructed with filtered back projection. Gadallah [12]
using double thresholding for image segmentation after denoising in Curvelet transform domain
applied in hepatic abcessed. Kaur [13] discussed about segmentation algorithmshave been
applied on Thyroid Scintigraphy and Ultrasound Images. Chen [14] developed a fully-automated
and efficient method for detecting contour of common carotid artery in the cross section view of
two-dimensional B-mode sonography. They evaluated 130 ultrasound images from three
healthy volunteers and thesegmentation results were compared to the boundaries outlined by
an expert. Teng [15] using image segmentation to discover regions of interest (ROI) using self-
organizing maps (SOM). They devise a two-stage SOM approach that can be used to precisely
identify the dominant colors of a medical image and then segment it into several small regions.
Becker [16] using an algorithm based on a 3D statistical shape model to segment the fetal
cerebellum on 3D ultrasound volumes. This model is adjusted using an ad hoc objective
function which is in turn optimized using the Nelder-Mead simplex algorithm. Kocer [17]
measured the effecr of filters to automate segmentation of DDH ultrasound images in order to
make it convenient for radiologic diagnosis. Gupta [18] developed an automatic segmentation of
SSP tendon ultrasound image to provide focused and more accurate diagnosis. The image
processing techniques were employed for automatic segmentation of SSP tendon. The image
processing techniques combines curvelet transform and mathematical concepts of logical and
morphological operators along with area filtering. Huang [19] developed a fully automated (i.e.
operator-independent) PS image segmentation forthe estimation of thyroid volume. Loizou [20]
proposed the best performing method that can be used for the segmentation of the IMC and the
atherosclerotic carotid plaque in ultrasound images and videos. Referring to the research that
has been done, it seems that most of the research carried out for advanced medical facilities In
our previous research [21-28] we also implemented image processing teqniques for improving
medical images quality. In this paper, we aim to explore the advantages of histogram
equalization method for improving image quality in low-resolution ultrasonography images.
Image histogram is described in a simple as a bar graph of the intensity of the pixels. Pixel
intensity plotted along the x-axis and the number of appearances for each intensity represented
on the y-axis. From a histogram can be determined relative frequency of occurrence (Relative)
of intensity on that image. The histogram can also show many things about the brightness and
contrast of an image. Therefore histogram is a valuable tool in image processing work either
qualitatively and quantitatively [29].
2. Research Method
2.1. Data Acquisition
Data used in this research is the ultrasonography images obtained from general
hospital “Prof. Margono Soekarjo” Purwokerto, Central Java Indonesia. Figure 1 shows an
example of ultrasonography image that used in our research. In the original images, there is
informations about patient’s name and hospital, medical records, etc. Therefore we need to crop
this kind of information. Figure 2 shows the result of image after we cropped the information
above.
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Figure 1. Original image Figure 2. Cropped image
2.2. Pre-Processing Image
The first step in the pre-processing image is changing the original image which is an
RGB image into gray scale image. In a grayscale image, each pixel has only one value in the
form of gray scale. Starting with black at the lowest intensity level until the white color with the
highest intensity level. The aim of converting RGB image to grayscale image is to simplify image
model to do digital image processing. Figure 3 shows the result of grayscale image. The next
stage is the stage of screening or filtering. A stage which is useful for reducing noise. In this
research we use Median Filter because this filter has the ability to reduce noise very well.
Figure 4 shows the result of median filter.
Figure 3. Grayscale image Figure 4. Median filter
2.3. Histogram Equalization
Histogram equalization is to change the image intensity values in order to make a
uniform distribution of intensity in the whole image. Histogram equalization obtained by
changing the degree of gray of a pixel (r) with the degree of gray new one (s) with a
transformation function T, which in this case s = T (r). Where r can be recovered from the
inverse transformation r s = T-1 (s) where, 0 ≤ s ≤ 1. Fo 0 ≤ ri ≤ 1 then 0 ≤ T (r) ≤ 1. This is to
ensure consistent mapping on the range allowed values [29]. Histogram equalization process
results will not be uniform or equal to the entire intensity. This technique can only redistribute
the intensity distribution of the initial histogram. If the initial histogram has several peaks and
valleys of the histogram equalization results will remain has peaks and valleys. However, the
peaks and valleys that shifted. Histogram equalization results will be disseminated. The purpose
of histogram equalization is to obtain equitable spread of the histogram so that each degree of
gray has a relatively equal number of pixels. Because histogram expressed chance pixels with a
certain degree of gray, the formula calculates the histogram flattening shown in Equation 1.
( ) (1)
In this case
Histogram equalization method that will be used in this research are as follows [29].
a. Enhance Contrast Using Histogram Equalization (ECHE)
This method increases the image contrast by changing the values in the image
intensity, or the values in the colormap of an indexed image, so that the histogram of the output
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image with histogram determined approach. If using the specifications defined histogram
(hgram) then the transformation T in the form of a grayscale will be minimal as shown in
Equation 2.
|c1(T(k))-co(k)| 2
Wherein, c0 is the cumulative histogram A, c1 is a cumulative total intensity hgram for all
k. If not using hgram, then hgram considered flat.
b. Contrast Limited Adaptive Histogram Equalization (CLAHE)
Adaptive histogram equalization is basically the same as ordinary histogram
equalization. It's just an adaptive histogram equalization, the image is divided into blocks (sub-
image) of size n x n, and then each block histogram equalization process is carried out. The
block size (n) can vary and each block size will give different results. Each block can overlap
some pixels in other blocks when combined using bilinear interpolation to eliminate artificially
induced boundaries. Contrast, especially in homogeneous areas, can be limited in order to
avoid noise that may be present in the image.
This research will generate 264 ultrasonography images which will be analyzed derived
from 6 sample images. In ECHE method produces 30 images while CLAHE produce 234
images as shown in Table 1.
Tabel1. The Parameters and Values Used
Method Values number of
Parameter 1
Values number of
Parameter 2
Image
number
Number of result
image
ECHE
5 values
(5, 10, 50, 100, 200)
- 6 5 x 6 = 30
CLAHE
ClipLimit 3 values :
(0.01, 0.5, 1)
Distribution 3 values :
(uniform, rayleigh,
exponential)
6 3 x 3 x 6 = 54
NumTiles 3 values:
([3 3], [8 8], [16 16])
Distribution 3 values:
(uniform, rayleigh,
exponential)
6 3 x 3 x 6 = 54
Nbins 3 values:
(100, 175, 256)
Distribution 3 values:
(uniform, rayleigh,
exponential))
6
3 x 3 x 6 = 54
Range 2 values:
(original, full)
Distribution 3 values:
(uniform, rayleigh,
exponential)
6 2 x 3 x 6 = 36
Alpha 3 values:
(0.2, 0.4, 0.8)
Distribution 2 values:
(rayleigh, exponential)
6 3 x 2 x 6 = 36
Total Number 264
3. Results and Discussion
Based on observational data from the image generated by digital image processing
such as histogram equalization, it can be observed that from each image that is expressed
visually nice when that image can be used to diagnose patients. Criteria for good and not
determined by medical practitioners in general hospital “Prof. Margono Soekarjo” Purwokerto,
Central Java, Indonesia. The image of the identified clearly marked with a tick (√) on the
contrary, the image does not provide the information marked with a dash (-). So also with
contrast and sharpness with three categories: low, medium, and high.
In addition to visually, the parameters of success can also be seen on the MSE and
PSNR. Peak Signal to Noise Ratio (PSNR) is the ratio between the maximum values of the
signal measured by the amount of noise that affects the signals. PSNR is usually measured in
decibels. In this research, PSNR is used to compare the image quality before and after
histogram equalization. Table 2 to Table 5 described the results analysis of ECHE method.
Table 2 and Table 3, visually the threshold value-10-200, producing images that are
relatively similar, but have different histograms. On the threshold value-5, the image is less clear
because at least the grouping of grades of gray. If using a threshold value-2 will produce a
binary image. Overall image is too dark on this method.
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Table 2. Performance of ECHE Method
No Threshold
Type of testing image (abdominal)
Image
1 2 3 4 5 6
1. 5 - - - - - -
2. 10 √ √ √ √ √ √
3. 50 √ √ √ √ √ √
4. 100 √ √ √ √ √ √
5. 200 √ √ √ √ √ √
Table 3. Contrast and Sharpness of ECHE Method
No Threshold
Type of testing image (abdominal)
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. 5 √ - - - - √ - - - - √ √
2. 10 √ - - - - √ - - √ - - √
3. 50 √ - - - - √ √ - - - - √
4. 100 √ - - - - √ - - √ - - √
5. 200 √ √ - - - - - √ √ - - -
Table 4. MSE Values of ECHE Method
No Threshold
Type of testing image (abdominal)
Image
1 2 3 4 5 6
1. 5 10982.9 11350.1 10748.3 11167.4 11246.4 12639.7
2. 10 9664.7 10163.7 9355.7 9889.9 10156.3 11346.1
3. 50 8920.3 9482.2 8570.5 9166.5 9555.9 10630.7
4. 100 8862.6 9415.3 8516.6 9062.4 9506.3 10566.4
5. 200 8795.0 9372.5 8443.5 9016.8 9465.3 10517.8
Table 5. PNSR values of ECHE Method
No Threshold
Type of testing image (abdominal)
Image
1 2 3 4 5 6
1. 5 7.75764 7.61480 7.85141 7.68528 7.65466 7.14744
2. 10 8.31288 8.09429 8.45403 8.21285 8.09745 7.61635
3. 50 8.66099 8.39569 8.83471 8.54273 8.36207 7.89917
4. 100 8.68918 8.42645 8.86212 8.59233 8.38468 7.92551
5. 200 8.72244 8.44620 8.89956 8.61425 8.40343 7.94556
According to Table 4 and Table 5, the results of images tested, the MSE will decrease
when the threshold value is enlarged. While the value of PSNR will be even greater when the
threshold value is enlarged. Lowest MSE value, and the highest PSNR is when using a
threshold of 200. This is because enlarge the threshold in the ECHE method as well as enlarge
the range of gray values. Table 6 to Table 25 described the results analysis of CLAHE method
Table 6. Performance of CLAHE Method (ClipLimit & Distribution)
No.
Parameter Values Type of testing image (abdominal)
ClipLimit Distribution
Image
1 2 3 4 5 6
1. 0.01 uniform √ √ √ √ √ √
2. 0.01 rayleigh √ √ √ √ - √
3. 0.01 exponential √ - √ √ √ √
4. 0.5 uniform - - - - - -
5. 0.5 rayleigh - - - - - -
6. 0.5 exponential - - - - - -
7. 1 uniform - - - - - -
8. 1 rayleigh - - - - - -
9. 1 exponential - - - - - -
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Table 7. Contrast and Sharpness of CLAHE Method (ClipLimit & Distribution)
No.
Parameter Values Type of testing image (abdominal)
ClipLimit Distribution
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. 0.01 uniform √ √ - - - - √ √ - - - -
2. 0.01 rayleigh √ - - √ - - √ √ - - - -
3. 0.01 exponential √ - - √ - - √ √ - - - -
4. 0.5 uniform - - √ √ - - - √ - √ √ -
5. 0.5 rayleigh -- - √ - - √ - - √ √ - -
6. 0.5 exponential - - √ - - √ - - √ √ - -
7. 1 uniform - - - - √ √ - - √ - - √
8. 1 rayleigh - - √ - - √ - - - √- √ -
9. 1 exponential - - √ - - √ - - - - √ √
According to Table 6 and Table 7, visually using parameter 0:01 ClipLimit valuable and
Distribution parameter with a value of uniform, Rayleigh, or exponential, producing images that
are relatively the same, but have different histograms. By raising the value of the parameter
ClipLimit of 0.5 and 1 the results were less clear because the image of the object and the
background becomes mixed. The level of contrast and sharpness of the image 1 (C1) and the
image 3 (C3) is different. The addition of the value of the parameter ClipLimit result in image
contrast and sharpness increases. While the use of the Distribution parameters also affects
contrast and sharpness of the image produced.
Table 8. MSE Values of CLAHE Method (ClipLimit & Distribution)
No.
Parameter Values Type of testing image (abdominal)
CL Dist
Image
1 2 3 4 5 6
1. 0.01 uni 13858.3 13849.2 13713.1 15512.3 13567.1 13606.8
2. 0.01 ray 9633.8 9636.2 9435.0 11005.5 9435.1 9327.1
3. 0.01 exp 11628.5 11551.8 11495.2 13254.3 11283.7 11344.1
4. 0.5 uni 10989.2 11468.7 10309.6 12343.5 11142.5 10822.1
5. 0.5 ray 8400.9 8709.0 7844.8 9656.5 8506.6 8173.7
6. 0.5 exp 9562.7 9978.8 8964.0 10953.2 9666.0 9398.8
7. 1 uni 11422.6 11905.5 10623.0 12656.5 11604.4 11550.6
8. 1 ray 8730.5 9042.8 8075.3 9886.4 8877.2 8809.4
9. 1 exp 10005.0 10424.2 9283.7 11272.3 8877.2 10167.8
Table 9. PSNR Values of CLAHE Method (ClipLimit & Distribution)
No.
Parameter Values Type of testing image (abdominal)
CL Dist
Image
1 2 3 4 5 6
1. 0.01 uni 6.74771 6.75055 6.79345 6.25803 6.83900 6.82723
2. 0.01 ray 8.32682 8.32573 8.41736 7.74869 8.41731 8.46733
3. 0.01 exp 7.50955 7.53829 7.55962 6.94123 7.64028 7.61708
4. 0.5 uni 7.75515 7.56966 8.03240 7.25041 7.69496 7.82169
5. 0.5 ray 8.92153 8.76507 9.21895 8.31660 8.86722 9.04057
6. 0.5 exp 8.35898 8.17400 8.63974 7.76939 8.31229 8.43405
7. 1 uni 7.58715 7.40730 7.90234 7.14167 7.51857 7.53874
8. 1 ray 8.75439 8.60173 9.09319 8.21440 8.68203 8.71533
9. 1 exp 8.16263 7.98437 8.48758 7.64468 8.68203 8.09253
According to Table 8 and Table 9, in the calculation of the value of MSE and PSNR of
CLAHE method with parameter ClipLimit and Distribution, the MSE is spread over a range of
7844.8 - 15512.3. While PNSR in the range of 6.25803 - 9.21895. Parameter distribution also
affect the value of MSE and PSNR.
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Table 10. Performance of CLAHE Method (NumTiles & Distribution)
No.
Parameter Values Type of testing image (abdominal)
NumTiles Distribution
Image
1 2 3 4 5 6
1. [3 3] uniform √ √ √ √ - √
2. [3 3] rayleigh √ √ √ √ - -
3. [3 3] exponential √ - √ √ √ √
4. [8 8] uniform √ √ √ √ √ √
5. [8 8] rayleigh √ √ √ √ √ √
6. [8 8] exponential √ √ √ √ √ √
7. [16 16] uniform - - - - - -
8. [16 16] rayleigh - - - - - -
9. [16 16] exponential - - - - - -
Table 11. Contrast and Sharpness of CLAHE Method (NumTiles & Distribution)
No
.
Parameter Values Type of testing image (abdominal)
NumTiles Distribution
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. [3 3] uniform √ - - √ - - - - √ √ - -
2. [3 3] rayleigh √ - - √ - - √ √ - - - -
3. [3 3] exponential √ √- - - - - - - √ √ - -
4. [8 8] uniform √ √ - - - - - - √ √ - -
5. [8 8] rayleigh √ √ - - - - √ - - √ - -
6. [8 8] exponential √ - - √ - - √ - - √ - -
7. [16 16] uniform √ - - √ - - - - √ - - √
8. [16 16] rayleigh √ - - √ - - √ - - √ - -
9. [16 16] exponential √ - - √ - - √ - - √ - -
According to Table 10 and Table 11, if the value on NumTiles worth [16, 16] the
resulting image is not good because it is too small kernel used or shared image too much. For
value [3 3] and [8 8] visually produces a better image than without equalization. By using the
parameters of contrast and sharpness, image 1 (C1) and the image 3 (C3) on average result in
images with low contrast and sharpness.
Table 12. MSE Values of CLAHE Method (NumTiles & Distribution)
No.
Parameter Values Type of testing image (abdominal)
NT Dist
Image
1 2 3 4 5 6
1. [3 3] uni 11153.4 12366.3 11468.1 11918.3 13451.3 9921.3
2. [3 3] ray 7981.7 9058.1 8295.3 8539.7 9940.6 7165.7
3. [3 3] exp 9256.3 10471.7 9687.4 9938.4 11515.9 8141.9
4. [8 8] uni 13858.0 14922.5 13870.1 14483.8 15475.3 13606.0
5. [8 8] ray 9633.6 10607.3 9736.1 10055.4 11054.8 9327.3
6. [8 8] exp 11630.5 12695.5 11754.5 12166.7 13192.0 11339.0
7. [16 16] uni 16276.2 17269.5 16063.0 16932.8 17833.4 15877.7
8. [16 16] ray 11080.4 11998.4 11019.1 11529.4 12450.0 10667.4
9. [16 16] exp 13837.5 14828.7 13732.3 14419.1 15345.7 13416.8
Table 13. PSNR Values of CLAHE Method (NumTiles & Distribution)
No
.
Parameter Values Type of testing image (abdominal)
NT Dist
Image
1 2 3 4 5 6
1. [3 3] uni 7.69072 7.2424 7.56987 7.40267 6.87716 8.19909
2. [3 3] ray 9.14384 8.59442 8.97646 8.85034 8.19067 9.61219
3. [3 3] exp 8.50039 7.96464 8.30272 8.19160 7.55182 9.05750
4. [8 8] uni 6.74778 6.42638 6.74400 6.55596 6.26840 6.82749
5. [8 8] ray 8.32690 7.90876 8.28092 8.14081 7.72929 8.46720
6. [8 8] exp 7.50880 7.12829 7.46277 7.31307 6.96171 7.61904
7. [16 16] uni 6.04927 5.79199 6.10654 5.87750 5.65246 6.15692
8. [16 16] ray 7.71926 7.37355 7.74334 7.54674 7.21310 7.88423
9. [16 16] exp 6.75421 6.45378 6.78737 6.57542 6.30494 6.88830
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According to Table 12 and Table 13, the results of the calculation of MSE and PSNR in
the image of the smallest MSE value obtained when NumTiles parameter-value [3 3], the largest
PSNR values were also obtained when the parameter NumTiles worth [3 3] with the Distribution
Rayleigh or exponential.
Table 14. Performance of CLAHE Method (Nbins & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Nbins Distribution
Image
1 2 3 4 5 6
1. 100 uniform - - - - - -
2. 100 rayleigh √ - √ √ - √
3. 100 exponential - - - - - -
4. 175 uniform - - - - - -
5. 175 rayleigh √ √ √ √ √ √
6. 175 exponential √ √ √ √ √ √
7. 256 uniform √ √ √ √ √ √
8. 256 rayleigh √ √ √ √ √ √
9. 256 exponential √ √ √ √ √ √
Table 15. Contrast and Sharpness of CLAHE Method (Nbins & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Nbins Distribution
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. 100 uniform √ √ - - - - √ - - √ - -
2. 100 rayleigh √ √ - - - - - - √ √ - -
3. 100 exponential √ - √ - - - √ √ - - -
4. 175 uniform √ √ - - - - - - √ √ - -
5. 175 rayleigh √ √ - - - - √ √ - - - -
6. 175 exponential - - √ √ - - - - √ √ - -
7. 256 uniform - - √ √ - - - - √ √ - -
8. 256 rayleigh - - √ √ - - - - √ √ - -
9. 256 exponential - - √ √ - - √ - - √ - -
According to Table 14 and Table 15, in combination Nbins parameters and Distribution
image is not good when the value Nbins 100, but when it was increased to 256 resulting in a
better image. In the assessment results based on image contrast and sharpness in image 1
(C1) and the image 3 (C3) never touch the category of high contrast and sharpness. The
contrast value will be higher when the value of the parameter Nbins enlarged, while the average
value of sharpness in middle category.
Table 16. MSE Values of CLAHE Method (Nbins & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Nb Dist
Image
1 2 3 4 5 6
1. 100 uni 17381.6 17204.2 17509.5 19250.2 17406.2 17594.4
2. 100 ray 11712.4 11593.3 11696.3 13234.0 11642.9 11674.0
3. 100 exp 14863.2 14612.2 15031.9 13234.0 14784.0 15038.2
4. 175 uni 15293.4 15257.8 15324.6 17094.1 15223.7 15335.6
5. 175 ray 10459.3 10437.1 10365.4 11916.8 10368.7 10314.7
6. 175 exp 12904.1 12817.4 12966.5 14698.7 12759.1 12913.6
7. 256 uni 13861.8 13848.2 13709.3 15508.4 13586.8 13586.3
8. 256 ray 9636.9 9634.1 9432.4 11002.7 9446.8 9315.9
9. 256 exp 11633.2 11552.0 11491.3 13250.2 11302.0 11323.2
According to Table 16 and Table 17, the smallest MSE value obtained when Nbins
worth 256, as well as the largest PSNR value. The average value of MSE greater when the
value Nbins minimized and PSNR greater when the enlarged Nbins value.
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Table 17. PSNR Values of CLAHE Method (Nbins & Distribution)
No.
Parameter Values Type of testing image (abdominal) Image
Nb Dist 1 2 3 4 5 6
1. 100 uni 5.76391 5.80847 5.73206 5.32046 5.75775 5.71106
2. 100 ray 7.47834 7.52272 7.48432 6.94788 7.50419 7.49261
3. 100 exp 6.44368 6.51765 6.39466 5.92799 6.46688 6.39285
4. 175 uni 6.31976 6.32988 6.31091 5.83634 6.33961 6.30778
5. 175 ray 7.96976 7.97902 8.00894 7.40321 8.00757 8.03022
6. 175 exp 7.05754 7.08679 7.03656 6.49201 7.10661 7.05431
7. 256 uni 6.74659 6.75087 6.79463 6.25912 6.83364 6.83378
8. 256 ray 8.32541 8.32666 8.41858 7.74980 8.41192 8.47253
9. 256 exp 7.50781 7.53822 7.56109 6.94257 7.63324 7.62510
Table 18. Performance of CLAHE Method (Range & Distribution)
No.
Parameter Values Type of testing image (abdominal) Image
Range Distribution 1 2 3 4 5 6
1. original uniform √ - √ √ - √
2. original rayleigh √ √ √ √ √ √
3. original exponential √ √ √ √ √ √
4. full uniform √ √ √ √ - √
5. full rayleigh √ - √ √ √ √
6. full exponential √ √ √ √ √ √
Table 19. Contrast and Sharpness of CLAHE Method (Range & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Range Distribution
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. original uniform - - √ √ - - √ - - √ - -
2. original rayleigh - - √ √ - - - - √ √ - -
3. original exponential - - √ √ - - - - √ √ - -
4. full uniform - - √ √ - - - - √ √ - -
5. full rayleigh √ - - - - √ - - √ √ - -
6. full exponential - - √ √ - - - - √ √ - -
According to Table 18 and Table 19, The results of histogram equalization with a
combination of parameters Range and Distribution almost all produce relatively the same
image, using either the original or full parameter combined with uniform parameters, rayleigh,
and exponential. For the assessment of the parameters in the image contrast and sharpness 1
(C1) and the image 3 (C3) on average tends to have the contrast and sharpness are moderate.
Table 20. MSE Values of CLAHE Method (Range & Distribution)
No.
Parameter values Type of testing image (abdominal) Image
Rng Dist 1 2 3 4 5 6
1. ori uni 14785.1 15106.0 13720.8 15519.2 15929.9 15097.5
2. ori ray 10359.4 10599.8 9442.1 11012.4 11439.0 10741.7
3. ori exp 12581.3 12839.1 11503.4 13261.9 13657.1 12907.5
4. full uni 14785.1 15106.0 13720.8 15519.2 15929.9 15097.5
5. full ray 10359.4 10599.8 9442.1 11012.4 11439.0 10741.7
6. full exp 12581.3 12839.1 11503.4 13261.9 13657.1 12907.5
Table 21. PSNR Values of CLAHE Method (Range & Distribution)
No
.
Parameter values Type of testing image (abdominal) Image
Rng Dist 1 2 3 4 5 6
1. ori uni 6.46656 6.37330 6.79101 6.25611 6.14266 6.37575
2. ori ray 8.01144 7.91183 8.41410 7.74600 7.58092 7.85405
3. ori exp 7.16753 7.07946 7.55653 6.93873 6.81122 7.05636
4. full uni 6.46656 6.37330 6.79101 6.25611 6.14266 6.37570
5. full ray 8.01144 7.91183 8.41410 7.74600 7.58092 7.85405
6. full exp 7.16753 7.07946 7.55653 6.93873 6.81122 7.05636
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According to Table 20 and Table 21, the results of MSE and PSNR calculation methods
CLAHE the parameter range and distribution to produce the highest MSE value and the lowest
PSNR in the Distribution uniform. In Rayleigh produce the same MSE and PSNR both original
and full.
Table 22. Performance of CLAHE Method (Alpha & Distribution)
No
.
Parameter Values Type of testing image (abdominal) Image
Alpha Distribution 1 2 3 4 5 6
1. 0.2 rayleigh - - - - - -
2. 0.2 exponential √ - √ √ - √
3. 0.4 rayleigh √ √ √ √ √ √
4. 0.4 exponential √ √ √ √ √ √
5. 0.8 rayleigh - - - - - -
6. 0.8 exponential √ √ √ √ √ √
Table 23. Contrast and Sharpness of CLAHE Method (Alpha & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Alpha Distribution
Contrast Sharpness
Low Medium High Low Medium High
C1 C3 C1 C3 C1 C3 C1 C3 C1 C3 C1 C3
1. 0.2 rayleigh √ - - - - √ √ √ - - -
2. 0.2 exponential - - √ - - √ - - √ √ - -
3. 0.4 rayleigh - - √ √ - - - - √ √ - -
4. 0.4 exponential - - √ √ - - - - √ √ - -
5. 0.8 rayleigh - √ √ - - - - √ √ - -
6. 0.8 exponential - - √ √ - - - - √ √ - -
According to Table 22 and Table 23, the combination of Alpha and Distribution
parameters of the resulting image is not good, the Alpha worth 0.2 and 0.8 with rayleigh
Distribution. The image becomes too dim to the value of 0.2, too light on the value of 0.8. While
the remaining combinations produce a good image. In contrast and sharpness assessment,
image 1 (C1) and the image 3 (C3), have an average contrast and sharpness with moderate
categories. But there are some who have the contrast and sharpness of low and high as the
value of Alpha 0.2 and 0.8.
Table 24. MSE Values of CLAHE Method (Alpha & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Alp Dist
Image
1 2 3 4 5 6
1. 0.2 ray 1462.6 2138.0 1389.9 2328.4 1065.0 1364.1
2. 0.2 exp 12730.2 13794.8 12602.6 14381.6 12402.7 12446.1
3. 0.4 ray 9636.6 10610.0 9439.2 11008.8 9427.6 9415.3
4. 0.4 exp 11630.4 12694.6 11504.4 13262.2 11275.7 11384.6
5. 0.8 ray 19716.2 20742.4 19458.3 21273.6 19776.4 19330.1
6. 0.8 exp 9552.7 10612.0 9432.9 11139.5 9157.3 9387.7
Table 25. PSNR Values of CLAHE Method (Alpha & Distribution)
No.
Parameter Values Type of testing image (abdominal)
Alp Dist
Image
1 2 3 4 5 6
1. 0.2 ray 16.5134 14.8646 16.7347 14.4942 17.8910 16.8163
2. 0.2 exp 7.1164 6.7676 7.1601 6.5867 7.2296 7.2144
3. 0.4 ray 8.3255 7.9076 8.4154 7.7474 8.4207 8.4264
4. 0.4 exp 7.5088 7.1286 7.5561 6.9386 7.6433 7.6016
5. 0.8 ray 5.2165 4.9962 5.2737 4.8863 5.2033 5.3024
6. 0.8 exp 8.3635 7.9068 8.4183 7.6961 8.5470 8.4391
According to Table 24 and Table 25, MSE and PSNR calculation methods CLAHE with
parameters Alpha and Distribution produces the smallest MSE value and the largest PNSR on
11. TELKOMNIKA ISSN: 1693-6930
Histogram Equalization for Improving Quality of Low-Resolution ... (Retno Supriyanti)
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Alpha 0.2, but in terms of the visual side, the image is too dark because of the histogram are
concentrated in the left area.
According to the results as described in all Tables above, we could make a comparison
between ECHE method and CLAHE method as shown in Table 26.
Table 26. Comparison between ECHE and CLAHE method
No
Parameter
Value
Average
MSE
Average
PSNR
VIsually
Medium
Contrast
Medium
Sharpness
C1 C3 C1 C3
1.
ECHE
9868.48 8.105240 6/6 x 100% = 100% - - √ -Thrshld 200
CLAHE
2. 1 ray 8903.60 8.676845 0/6 x 100% = 0 √ - - √
3. [3 3] ray 8496.85 8.894653 4/6 x 100% = 66,6% - √ - -
4. 256 ray 9744.80 8.284150 6/6 x 100% = 100% √ √ √ √
5. ori ray 10599.07 7.919723 6/6 x 100% = 100% √ √ √ √
6. full ray 10599.07 7.919723 6/6 x 100% = 100% - - √ √
7. 0.2 ray 1624.67 16.219033 0/6 x 100% = 0% - - - -
4. Conclusions
According to our results as discussed above, we conclude that (i) histogram
equalization on a 2D image of Medical Ultrasound (USG) can improve image quality and make it
easier for medical practitioners diagnose the disease. (ii) By comparing two methods of
histogram equalization, concluded CLAHE method is better than the ECHE method. (iii) The
best combination in CLAHE method is, using parameter Nbins worth 256 and Distribution
Rayleigh with MSE value is 9744.80 and PSNR value is 8.284150.
Aknowledgment
This work is supported by Directorate General of Higher Education through Hibah
Strategis Nasional (STRANAS).
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