The document discusses various topics relating to creative media production including raster and vector graphics, anti-aliasing, bit depth, aspect ratio, file formats, color models, and Adobe software applications like Photoshop, Illustrator, and InDesign. Specifically, it provides technical definitions and explanations of these key concepts and tools used in digital graphics and design.
Image Authentication Using Digital Watermarkingijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
This document summarizes a research paper on progressive image compression using wavelet transforms and SPIHT encoding. It discusses how:
1. Image compression reduces file sizes while maintaining acceptable quality, allowing more images to be stored. Wavelet transforms break images into different frequency bands, and SPIHT exploits properties of wavelet-transformed images to efficiently encode them.
2. Progressive compression methods convert images to intermediate formats and allow users to choose compressed images without noticeable quality loss. SPIHT provides fast encoding and decoding as well as embedded coding to optimize transmission.
3. SPIHT uses uniform scalar quantization and provides a simple, fast way to compress images with embedded bitstreams and progressive transmission at variable bitrates while maintaining good
The document describes a decision tree based technique for removing impulse noise from digital images. It uses a 3x3 pixel mask to detect noisy pixels and then employs an edge-preserving filter to reconstruct pixel values. The technique was implemented on an FPGA and tested on test images corrupted with random valued impulse noise. It achieved better noise removal compared to other lower complexity methods while preserving image details due to its accurate noise detection and minimal hardware requirements.
Digital image processing involves compressing images to reduce file sizes. Image compression removes redundant data using three main techniques: coding redundancy reduction assigns shorter codes to more common pixel values; spatial and temporal redundancy reduction exploits correlations between neighboring pixel values; and irrelevant information removal discards visually unimportant data. Compression is achieved by an encoder that applies these techniques, while a decoder reconstructs the image for viewing. Popular compression methods include Huffman coding and arithmetic coding. Compression allows storage and transmission of images and video using less data while maintaining acceptable visual quality.
Images are visual representations that can be used to record and present information. There are various techniques for acquiring, processing, and manipulating digital images with computers. The fundamental steps in digital image processing typically involve image acquisition, enhancement, restoration, compression, and segmentation. Imaging systems cover a wide range of the electromagnetic spectrum and light is commonly used for imaging due to its safe, reliable, and controllable properties.
This document provides an overview of a research project on image compression. It discusses image compression techniques including lossy and lossless compression. It describes using discrete wavelet transform, lifting wavelet transform, and stationary wavelet transform for image transformation. Experiments were conducted to compare the compression ratio and processing time of different combinations of wavelet transforms, vector quantization, and Huffman/Arithmetic coding. The results were analyzed to evaluate the compression performance and efficiency of the different methods.
here it introduces an efficient multi-resolution watermarking methodology for copyright protection of digital images. By adapting the watermark signal to the wavelet coefficients, the proposed method is highly image adaptive and the watermark signal can be strengthen in the most significant parts of the image. As this property also increases the watermark visibility, usage of the human visual system is incorporated to prevent perceptual visibility of embedded watermark signal. Experimental results show that the proposed system preserves the image quality and is vulnerable against most common image processing distortions. Furthermore, the hierarchical nature of wavelet transform allows for detection of watermark at various resolutions, resulting in reduction of the computational load needed for watermark detection based on the noise level. The performance of the proposed system is shown to be superior to that of other available schemes reported in the literature.
REGION OF INTEREST BASED COMPRESSION OF MEDICAL IMAGE USING DISCRETE WAVELET ...ijcsa
Image abbreviation is utilized for reducing the size of a file without demeaning the quality of the image to an objectionable level. The depletion in file size permits more images to be deposited in a given number of spaces. It also minimizes the time necessary for images to be transferred. There are different ways of abbreviating image files. For the use of Internet, the two most common abbreviated graphic image formats are the JPEG formulation and the GIF formulation. The JPEG procedure is more often utilized or
photographs, while the GIF method is commonly used for logos, symbols and icons but at the same time
they are not preferred as they use only 256 colors. Other procedures for image compression include the
utilization of fractals and wavelets. These procedures have not profited widespread acceptance for the
utilization on the Internet. Abbreviating an image is remarkably not similar than the compressing raw
binary data. General-purpose abbreviation techniques can be utilized to compress images, the obtained
result is less than the optimal. This is because of the images have certain analytical properties, which can
be exploited by encoders specifically designed only for them. Also, some of the finer details of the image
can be renounced for the sake of storing a little more bandwidth or deposition space. In the paper,
compression is done on medical image and the compression technique that is used to perform compression
is discrete wavelet transform and discrete cosine transform which compresses the data efficiently without
reducing the quality of an image
Image Authentication Using Digital Watermarkingijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
This document summarizes a research paper on progressive image compression using wavelet transforms and SPIHT encoding. It discusses how:
1. Image compression reduces file sizes while maintaining acceptable quality, allowing more images to be stored. Wavelet transforms break images into different frequency bands, and SPIHT exploits properties of wavelet-transformed images to efficiently encode them.
2. Progressive compression methods convert images to intermediate formats and allow users to choose compressed images without noticeable quality loss. SPIHT provides fast encoding and decoding as well as embedded coding to optimize transmission.
3. SPIHT uses uniform scalar quantization and provides a simple, fast way to compress images with embedded bitstreams and progressive transmission at variable bitrates while maintaining good
The document describes a decision tree based technique for removing impulse noise from digital images. It uses a 3x3 pixel mask to detect noisy pixels and then employs an edge-preserving filter to reconstruct pixel values. The technique was implemented on an FPGA and tested on test images corrupted with random valued impulse noise. It achieved better noise removal compared to other lower complexity methods while preserving image details due to its accurate noise detection and minimal hardware requirements.
Digital image processing involves compressing images to reduce file sizes. Image compression removes redundant data using three main techniques: coding redundancy reduction assigns shorter codes to more common pixel values; spatial and temporal redundancy reduction exploits correlations between neighboring pixel values; and irrelevant information removal discards visually unimportant data. Compression is achieved by an encoder that applies these techniques, while a decoder reconstructs the image for viewing. Popular compression methods include Huffman coding and arithmetic coding. Compression allows storage and transmission of images and video using less data while maintaining acceptable visual quality.
Images are visual representations that can be used to record and present information. There are various techniques for acquiring, processing, and manipulating digital images with computers. The fundamental steps in digital image processing typically involve image acquisition, enhancement, restoration, compression, and segmentation. Imaging systems cover a wide range of the electromagnetic spectrum and light is commonly used for imaging due to its safe, reliable, and controllable properties.
This document provides an overview of a research project on image compression. It discusses image compression techniques including lossy and lossless compression. It describes using discrete wavelet transform, lifting wavelet transform, and stationary wavelet transform for image transformation. Experiments were conducted to compare the compression ratio and processing time of different combinations of wavelet transforms, vector quantization, and Huffman/Arithmetic coding. The results were analyzed to evaluate the compression performance and efficiency of the different methods.
here it introduces an efficient multi-resolution watermarking methodology for copyright protection of digital images. By adapting the watermark signal to the wavelet coefficients, the proposed method is highly image adaptive and the watermark signal can be strengthen in the most significant parts of the image. As this property also increases the watermark visibility, usage of the human visual system is incorporated to prevent perceptual visibility of embedded watermark signal. Experimental results show that the proposed system preserves the image quality and is vulnerable against most common image processing distortions. Furthermore, the hierarchical nature of wavelet transform allows for detection of watermark at various resolutions, resulting in reduction of the computational load needed for watermark detection based on the noise level. The performance of the proposed system is shown to be superior to that of other available schemes reported in the literature.
REGION OF INTEREST BASED COMPRESSION OF MEDICAL IMAGE USING DISCRETE WAVELET ...ijcsa
Image abbreviation is utilized for reducing the size of a file without demeaning the quality of the image to an objectionable level. The depletion in file size permits more images to be deposited in a given number of spaces. It also minimizes the time necessary for images to be transferred. There are different ways of abbreviating image files. For the use of Internet, the two most common abbreviated graphic image formats are the JPEG formulation and the GIF formulation. The JPEG procedure is more often utilized or
photographs, while the GIF method is commonly used for logos, symbols and icons but at the same time
they are not preferred as they use only 256 colors. Other procedures for image compression include the
utilization of fractals and wavelets. These procedures have not profited widespread acceptance for the
utilization on the Internet. Abbreviating an image is remarkably not similar than the compressing raw
binary data. General-purpose abbreviation techniques can be utilized to compress images, the obtained
result is less than the optimal. This is because of the images have certain analytical properties, which can
be exploited by encoders specifically designed only for them. Also, some of the finer details of the image
can be renounced for the sake of storing a little more bandwidth or deposition space. In the paper,
compression is done on medical image and the compression technique that is used to perform compression
is discrete wavelet transform and discrete cosine transform which compresses the data efficiently without
reducing the quality of an image
Digital Image Forensics: camera fingerprint and its robustness Francesco Forestieri
1. The document discusses camera fingerprint analysis, which is used in digital forensics to identify the source device of digital images.
2. It explains that each image sensor has a unique photo response non-uniformity (PRNU) pattern that is imprinted onto every image taken, acting as a sensor fingerprint.
3. The process of linking devices involves calculating a camera reference pattern from multiple images, extracting the noise pattern from a target image, and finding the correlation between the reference pattern and target noise to determine if they match.
This document discusses image compression using a Raspberry Pi processor. It begins with an abstract stating that image compression is needed to reduce file sizes for storage and transmission while retaining image quality. The document then discusses various image compression techniques like discrete wavelet transform (DWT) and discrete cosine transform (DCT), as well as JPEG compression. It states that the Raspberry Pi allows implementing DWT to provide JPEG format images using OpenCV. The document provides details of the image compression method tested, which involves capturing images with a USB camera connected to the Raspberry Pi, compressing the images using DWT and wavelet transforms, transmitting the compressed images over the internet, decompressing the images on a server, and displaying the decompressed images
AN EMERGING TREND OF FEATURE EXTRACTION METHOD IN VIDEO PROCESSINGcscpconf
Recently the progress in technology and flourishing applications open up new forecast and defy
for the image and video processing community. Compared to still images, video sequences
afford more information about how objects and scenarios change over time. Quality of video is
very significant before applying it to any kind of processing techniques. This paper deals with
two major problems in video processing they are noise reduction and object segmentation on
video frames. The segmentation of objects is performed using foreground segmentation based
and fuzzy c-means clustering segmentation is compared with the proposed method Improvised
fuzzy c – means segmentation based on color. This was applied in the video frame to segment
various objects in the current frame. The proposed technique is a powerful method for image
segmentation and it works for both single and multiple feature data with spatial information.
The experimental result was conducted using various noises and filtering methods to show which is best suited among others and the proposed segmentation approach generates good quality segmented frames.
Fractal Image Compression Using Quadtree DecompositionHarshit Varshney
This document summarizes a student project on fractal image compression using quadtree decomposition. It introduces fractal image compression and quadtree decomposition partitioning. The proposed algorithm divides the original image using quadtree decomposition with a threshold of 0.2 and minimum and maximum block sizes of 2 and 64. It records fractal coding information and uses Huffman coding for compression. Experimental results on test images show compression ratios from 2.45 to 12.79 and reconstruction PSNR values from 22.24 to 27.35.
The document proposes a selective data pruning-based compression scheme to improve rate-distortion performance. It involves pruning original frames to a smaller size before compression by dropping rows or columns. After decoding, frames are interpolated back to the original size using an edge-directed interpolation method. A novel high-order interpolation is also introduced to adapt to multiple edge directions. Simulation results validate the effectiveness of the proposed methods in image interpolation and video coding applications by achieving high quality from lower bitrates compared to existing techniques.
Thesis on Image compression by Manish MystManish Myst
The document discusses using neural networks for image compression. It describes how previous neural network methods divided images into blocks and achieved limited compression. The proposed method applies edge detection, thresholding, and thinning to images first to reduce their size. It then uses a single-hidden layer feedforward neural network with an adaptive number of hidden neurons based on the image's distinct gray levels. The network is trained to compress the preprocessed image block and reconstruct the original image at the receiving end. This adaptive approach aims to achieve higher compression ratios than previous neural network methods.
Iaetsd performance analysis of discrete cosineIaetsd Iaetsd
The document discusses image compression using the discrete cosine transform (DCT). It provides background on image compression and outlines the DCT technique. The DCT transforms an image into elementary frequency components, removing spatial redundancy. The document analyzes the performance of compressing different images using DCT in Matlab by measuring metrics like PSNR. Compression using DCT with different window sizes achieved significant PSNR values.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
call for paper 2012, hard copy of journal, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Abstract: The increasing amount of applications using digital multimedia technologies has accentuated the need to provide copyright protection to multimedia data. This paper reviews one of the data hiding techniques - digital image watermarking. Through this paper we will explore some basic concepts of digital image watermarking techniques.Two different methods of digital image watermarking namely spatial domain watermarking and transform domain watermarking are briefly discussed in this paper. Furthermore, two different algorithms for a digital image watermarking have also been discussed. Also the comparision between the different algorithms,tests performed for the robustness and the applications of the digital image watermarking have also been discussed.
The document provides information about a seminar presentation on digital image processing. It discusses the following key points:
- The presentation was given by two students and covered topics like the introduction, history, functional categories, steps, necessity, filtering, technologies, advantages/disadvantages, and applications of digital image processing.
- A brief history of digital image processing is provided, noting its origins in newspaper printing and early uses in space applications and medical imaging.
- Functional categories of digital image processing include image enhancement, restoration, and information extraction. Key steps involve acquisition, enhancement, restoration, compression, and segmentation.
- Technologies discussed include pixelization, component analysis, independent component analysis, hidden Markov models,
image compression using matlab project reportkgaurav113
The document discusses JPEG image compression and its implementation in MATLAB. It describes the steps taken to encode and decode grayscale images using the JPEG baseline standard in MATLAB. These include dividing images into 8x8 blocks, applying the discrete cosine transform, quantizing the results, and entropy encoding the data. Encoding compression ratios and processing times are compared between classic and fast DCT approaches. The project also examines how quantization coefficients affect the restored image quality.
Generating a time shrunk lecture video by eventYara Ali
The document describes a system for generating time-shortened lecture videos through event detection. The system records high-resolution lecture footage and then analyzes it to detect speech periods using voice activity detection and chalkboard writing periods using object detection and segmentation techniques. These event detection techniques allow the system to automatically generate a shortened lecture video by removing non-event periods and fast-forwarding writing periods. Evaluation of the system on test lecture recordings showed it could generate videos 20-30% shorter than the originals, similar to manual shortening by humans.
Neural Network Based Noise Identification in Digital ImagesIDES Editor
Image noise is unwanted information in an image
and can occur at any moment of time such as during image
capture, transmission, or processing and it may or may not
depend on image content. In order to remove the noise from
the noisy image, prior knowledge about the nature of noise
must be known otherwise noise removal causes the image
blurring. Identifying nature of noise is a challenging problem.
Many researchers have proposed their ideas on image noise
identification and each of the work has its assumptions,
advantages and limitations. In this paper, we proposed a new
methodology based on neural network for identifying the
different types of noise such as Non Gaussian, Gaussian white,
Salt and Pepper and Speckle noise.
IMAGE COMPRESSION AND DECOMPRESSION SYSTEMVishesh Banga
Image compression is the application of Data compression on digital images. In effect, the objective is to reduce redundancy of the image data in order to be able to store or transmit data in an efficient form.
Multilayer bit allocation for video encodingIJMIT JOURNAL
Video compression approach removes spatial and temporal redundancy based on the signal statistical correlation. Bit allocation technique adopts a visual distortion model for a better rate visual distortion video coding. Visual distortion model uses both motion and the texture structures in the video sequences. The existing video coding mechanisms reduces the bit rate for video coding. However to get better video compression ratio there is a need for multilayer compression technique. In this paper we proposed a multilayer bit allocation video coding mechanism. The proposed model reduces the bit allocation for video coding by retaining the same video quality. The experimental results using the proposed model reduced the bit rate by 3% to 4%. The result are promising. Finally we conclude with conclusion and future work.
The objective of this work is to propose an image
denoising technique and compare it with image denoising
using ridgelets. The proposed method uses slantlet transform
instead of wavelets in ridgelet transform. Experimental result
shows that the proposed method is more effective than ridgelets
in noise removal. The proposed method is effective in
compressing images while preserving edges.
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
This document discusses wavelet transforms and fast wavelet transforms for image compression. It provides background on discrete wavelet transforms (DWT) and fast wavelet transforms. DWT is useful for image compression because it concentrates image energy into low-frequency coefficients. Compression is achieved by quantizing coefficients, prioritizing low-frequency ones. Popular image compression techniques like JPEG2000 use DWT. Fast wavelet transforms like Mallat's algorithm allow faster image analysis than DWT. The document reviews various image compression techniques and their performance in terms of compression ratio and image quality.
This document discusses an enhanced technique for secure and reliable watermarking using Modified Haar Wavelet Transform (MFHWT). The proposed technique embeds a watermark into an original image using discrete wavelet transform (DWT) and wavelet packet transform (WPT) according to the size of the watermark. MFHWT is a memory efficient, fast, and simple transform. The watermarking process involves embedding and extraction processes. Various watermarking techniques in different transform domains are discussed, including DWT and WPT. The proposed algorithm uses MFHWT for decomposition and reconstruction. Image quality is measured using metrics like MSE and PSNR, with higher PSNR indicating better quality. The technique achieves robustness
This document provides an overview of image denoising techniques. It discusses different types of noise that can affect images, such as amplifier noise, impulsive noise, and speckle noise. It also describes various denoising methodologies, including spatial filtering techniques like mean and median filters, as well as transform domain filtering and wavelet thresholding. Spatial filters can smooth noise but also blur edges, while wavelet thresholding can preserve edges while removing noise. The document reviews noise models, denoising methods, and provides insights to determine the most effective approach based on the noise characteristics.
James Fox took photographs during a trip to Media City UK for a photography college project. He chose 10 photos and edited them in Photoshop, applying effects like grayscale and sepia. He evaluated the strengths of each photo, noting how composition and editing enhanced qualities like brightness, boldness, and depth of field. His aim is to be more spontaneous with camera settings for future projects.
Round Table India is a service organization comprised of young professionals focused on community service, fellowship, and international relations. The Baroda Young Turks Round Table #201 chapter supports education initiatives, empowers women and children, provides disaster relief, and hosts an annual golf tournament to raise funds for these causes. Past tournaments have been well attended by dignitaries and generated over $50,000 for educational programs.
Digital Image Forensics: camera fingerprint and its robustness Francesco Forestieri
1. The document discusses camera fingerprint analysis, which is used in digital forensics to identify the source device of digital images.
2. It explains that each image sensor has a unique photo response non-uniformity (PRNU) pattern that is imprinted onto every image taken, acting as a sensor fingerprint.
3. The process of linking devices involves calculating a camera reference pattern from multiple images, extracting the noise pattern from a target image, and finding the correlation between the reference pattern and target noise to determine if they match.
This document discusses image compression using a Raspberry Pi processor. It begins with an abstract stating that image compression is needed to reduce file sizes for storage and transmission while retaining image quality. The document then discusses various image compression techniques like discrete wavelet transform (DWT) and discrete cosine transform (DCT), as well as JPEG compression. It states that the Raspberry Pi allows implementing DWT to provide JPEG format images using OpenCV. The document provides details of the image compression method tested, which involves capturing images with a USB camera connected to the Raspberry Pi, compressing the images using DWT and wavelet transforms, transmitting the compressed images over the internet, decompressing the images on a server, and displaying the decompressed images
AN EMERGING TREND OF FEATURE EXTRACTION METHOD IN VIDEO PROCESSINGcscpconf
Recently the progress in technology and flourishing applications open up new forecast and defy
for the image and video processing community. Compared to still images, video sequences
afford more information about how objects and scenarios change over time. Quality of video is
very significant before applying it to any kind of processing techniques. This paper deals with
two major problems in video processing they are noise reduction and object segmentation on
video frames. The segmentation of objects is performed using foreground segmentation based
and fuzzy c-means clustering segmentation is compared with the proposed method Improvised
fuzzy c – means segmentation based on color. This was applied in the video frame to segment
various objects in the current frame. The proposed technique is a powerful method for image
segmentation and it works for both single and multiple feature data with spatial information.
The experimental result was conducted using various noises and filtering methods to show which is best suited among others and the proposed segmentation approach generates good quality segmented frames.
Fractal Image Compression Using Quadtree DecompositionHarshit Varshney
This document summarizes a student project on fractal image compression using quadtree decomposition. It introduces fractal image compression and quadtree decomposition partitioning. The proposed algorithm divides the original image using quadtree decomposition with a threshold of 0.2 and minimum and maximum block sizes of 2 and 64. It records fractal coding information and uses Huffman coding for compression. Experimental results on test images show compression ratios from 2.45 to 12.79 and reconstruction PSNR values from 22.24 to 27.35.
The document proposes a selective data pruning-based compression scheme to improve rate-distortion performance. It involves pruning original frames to a smaller size before compression by dropping rows or columns. After decoding, frames are interpolated back to the original size using an edge-directed interpolation method. A novel high-order interpolation is also introduced to adapt to multiple edge directions. Simulation results validate the effectiveness of the proposed methods in image interpolation and video coding applications by achieving high quality from lower bitrates compared to existing techniques.
Thesis on Image compression by Manish MystManish Myst
The document discusses using neural networks for image compression. It describes how previous neural network methods divided images into blocks and achieved limited compression. The proposed method applies edge detection, thresholding, and thinning to images first to reduce their size. It then uses a single-hidden layer feedforward neural network with an adaptive number of hidden neurons based on the image's distinct gray levels. The network is trained to compress the preprocessed image block and reconstruct the original image at the receiving end. This adaptive approach aims to achieve higher compression ratios than previous neural network methods.
Iaetsd performance analysis of discrete cosineIaetsd Iaetsd
The document discusses image compression using the discrete cosine transform (DCT). It provides background on image compression and outlines the DCT technique. The DCT transforms an image into elementary frequency components, removing spatial redundancy. The document analyzes the performance of compressing different images using DCT in Matlab by measuring metrics like PSNR. Compression using DCT with different window sizes achieved significant PSNR values.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
call for paper 2012, hard copy of journal, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Abstract: The increasing amount of applications using digital multimedia technologies has accentuated the need to provide copyright protection to multimedia data. This paper reviews one of the data hiding techniques - digital image watermarking. Through this paper we will explore some basic concepts of digital image watermarking techniques.Two different methods of digital image watermarking namely spatial domain watermarking and transform domain watermarking are briefly discussed in this paper. Furthermore, two different algorithms for a digital image watermarking have also been discussed. Also the comparision between the different algorithms,tests performed for the robustness and the applications of the digital image watermarking have also been discussed.
The document provides information about a seminar presentation on digital image processing. It discusses the following key points:
- The presentation was given by two students and covered topics like the introduction, history, functional categories, steps, necessity, filtering, technologies, advantages/disadvantages, and applications of digital image processing.
- A brief history of digital image processing is provided, noting its origins in newspaper printing and early uses in space applications and medical imaging.
- Functional categories of digital image processing include image enhancement, restoration, and information extraction. Key steps involve acquisition, enhancement, restoration, compression, and segmentation.
- Technologies discussed include pixelization, component analysis, independent component analysis, hidden Markov models,
image compression using matlab project reportkgaurav113
The document discusses JPEG image compression and its implementation in MATLAB. It describes the steps taken to encode and decode grayscale images using the JPEG baseline standard in MATLAB. These include dividing images into 8x8 blocks, applying the discrete cosine transform, quantizing the results, and entropy encoding the data. Encoding compression ratios and processing times are compared between classic and fast DCT approaches. The project also examines how quantization coefficients affect the restored image quality.
Generating a time shrunk lecture video by eventYara Ali
The document describes a system for generating time-shortened lecture videos through event detection. The system records high-resolution lecture footage and then analyzes it to detect speech periods using voice activity detection and chalkboard writing periods using object detection and segmentation techniques. These event detection techniques allow the system to automatically generate a shortened lecture video by removing non-event periods and fast-forwarding writing periods. Evaluation of the system on test lecture recordings showed it could generate videos 20-30% shorter than the originals, similar to manual shortening by humans.
Neural Network Based Noise Identification in Digital ImagesIDES Editor
Image noise is unwanted information in an image
and can occur at any moment of time such as during image
capture, transmission, or processing and it may or may not
depend on image content. In order to remove the noise from
the noisy image, prior knowledge about the nature of noise
must be known otherwise noise removal causes the image
blurring. Identifying nature of noise is a challenging problem.
Many researchers have proposed their ideas on image noise
identification and each of the work has its assumptions,
advantages and limitations. In this paper, we proposed a new
methodology based on neural network for identifying the
different types of noise such as Non Gaussian, Gaussian white,
Salt and Pepper and Speckle noise.
IMAGE COMPRESSION AND DECOMPRESSION SYSTEMVishesh Banga
Image compression is the application of Data compression on digital images. In effect, the objective is to reduce redundancy of the image data in order to be able to store or transmit data in an efficient form.
Multilayer bit allocation for video encodingIJMIT JOURNAL
Video compression approach removes spatial and temporal redundancy based on the signal statistical correlation. Bit allocation technique adopts a visual distortion model for a better rate visual distortion video coding. Visual distortion model uses both motion and the texture structures in the video sequences. The existing video coding mechanisms reduces the bit rate for video coding. However to get better video compression ratio there is a need for multilayer compression technique. In this paper we proposed a multilayer bit allocation video coding mechanism. The proposed model reduces the bit allocation for video coding by retaining the same video quality. The experimental results using the proposed model reduced the bit rate by 3% to 4%. The result are promising. Finally we conclude with conclusion and future work.
The objective of this work is to propose an image
denoising technique and compare it with image denoising
using ridgelets. The proposed method uses slantlet transform
instead of wavelets in ridgelet transform. Experimental result
shows that the proposed method is more effective than ridgelets
in noise removal. The proposed method is effective in
compressing images while preserving edges.
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
This document discusses wavelet transforms and fast wavelet transforms for image compression. It provides background on discrete wavelet transforms (DWT) and fast wavelet transforms. DWT is useful for image compression because it concentrates image energy into low-frequency coefficients. Compression is achieved by quantizing coefficients, prioritizing low-frequency ones. Popular image compression techniques like JPEG2000 use DWT. Fast wavelet transforms like Mallat's algorithm allow faster image analysis than DWT. The document reviews various image compression techniques and their performance in terms of compression ratio and image quality.
This document discusses an enhanced technique for secure and reliable watermarking using Modified Haar Wavelet Transform (MFHWT). The proposed technique embeds a watermark into an original image using discrete wavelet transform (DWT) and wavelet packet transform (WPT) according to the size of the watermark. MFHWT is a memory efficient, fast, and simple transform. The watermarking process involves embedding and extraction processes. Various watermarking techniques in different transform domains are discussed, including DWT and WPT. The proposed algorithm uses MFHWT for decomposition and reconstruction. Image quality is measured using metrics like MSE and PSNR, with higher PSNR indicating better quality. The technique achieves robustness
This document provides an overview of image denoising techniques. It discusses different types of noise that can affect images, such as amplifier noise, impulsive noise, and speckle noise. It also describes various denoising methodologies, including spatial filtering techniques like mean and median filters, as well as transform domain filtering and wavelet thresholding. Spatial filters can smooth noise but also blur edges, while wavelet thresholding can preserve edges while removing noise. The document reviews noise models, denoising methods, and provides insights to determine the most effective approach based on the noise characteristics.
James Fox took photographs during a trip to Media City UK for a photography college project. He chose 10 photos and edited them in Photoshop, applying effects like grayscale and sepia. He evaluated the strengths of each photo, noting how composition and editing enhanced qualities like brightness, boldness, and depth of field. His aim is to be more spontaneous with camera settings for future projects.
Round Table India is a service organization comprised of young professionals focused on community service, fellowship, and international relations. The Baroda Young Turks Round Table #201 chapter supports education initiatives, empowers women and children, provides disaster relief, and hosts an annual golf tournament to raise funds for these causes. Past tournaments have been well attended by dignitaries and generated over $50,000 for educational programs.
Ansel Adams was a renowned American photographer known for his black and white landscapes of the American West. He helped pioneer technical methods like the zone system which gave photographers more control over exposures and developed the idea of visualizing compositions before taking the photo. Adams authored books on photography and received numerous honors including the Presidential Medal of Freedom. He was highly influential as both a photographer and teacher.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like anxiety and depression.
This assignment brief outlines tasks for students to complete pre-production work for a short film. It includes:
1) Creating a budget and production plan outlining roles, equipment, and costs.
2) Developing pre-production materials for the short film like scripts, storyboards, schedules.
3) Analyzing how room acoustics affect sound recording quality by recording in different environments.
4) Editing the recordings with effects and sequencing them to demonstrate editing skills.
The purpose is to enhance organizational and planning skills for film production while exploring the impact of sound recording environments and developing audio editing abilities. Meeting deadlines and grading criteria are essential for successfully completing the assignment.
Raster images represent images as grids of pixels and correspond directly to what is displayed on a screen. Vector images use geometric primitives and mathematical equations to represent images. Both formats have advantages and limitations depending on the situation. Anti-aliasing is a technique used to minimize aliasing artifacts when representing high-resolution images at lower resolutions.
This assignment brief outlines tasks for students to complete pre-production work for a short film. It includes:
1) Creating a budget and production plan outlining roles, equipment, and costs.
2) Developing pre-production documents for the short film like scripts, storyboards, schedules.
3) Recording dialogue in different environments and analyzing how acoustics affect sound quality.
4) Editing the recordings with effects and compiling them to demonstrate editing skills. Regular production meetings must be documented to track progress. Completing all tasks helps develop skills in planning, communication, problem solving, and independent learning.
This document provides information about various topics related to digital media production, including:
- It discusses raster images and how they represent digital images as a series of pixels arranged in a grid, while vector images use geometric primitives.
- It covers concepts like resolution, file formats, color models, and anti-aliasing as they relate to digital images. Common file formats discussed include JPEG, GIF, TIFF, EPS, and PSD.
- Graphics editing and design software are described, including Adobe Photoshop, Illustrator, and InDesign. Their features and uses for image editing, vector graphics, and page layout are summarized.
The document discusses several key topics related to digital images:
- Raster images are composed of pixels arranged in a grid, while vector images use mathematical descriptions of lines, curves and shapes. Raster images lose quality when scaled while vector images maintain quality.
- Resolution refers to the number of pixels per inch in a raster image, affecting quality of on-screen and printed display. Higher resolutions have more pixels and finer detail.
- Aspect ratio expresses the proportional relationship between an image's width and height, such as 16:9 for HDTV. Formats with unequal ratios require enlarging or adding borders for presentation.
- Common file formats include GIF for simple graphics, JPEG for photographs
The document discusses various topics relating to raster and vector images, including:
- Raster images are composed of pixels while vector images are composed of mathematical objects. Vector images can be scaled without quality loss.
- Common file formats for raster images include JPEG, TIFF, PNG, and GIF while common vector formats are EPS, AI, and PDF.
- Other topics covered include color models (RGB, CMYK), resolution, aspect ratio, and image editing software like Photoshop, Illustrator, and InDesign.
The document discusses key concepts in digital graphics and design including:
- The differences between raster (bitmap) and vector graphics and their uses.
- Anti-aliasing techniques to reduce jagged edges in raster images.
- Factors that impact image quality such as resolution, aspect ratio, and file formats.
- Color models like RGB and CMYK.
- Popular design software like Adobe Photoshop, Illustrator, and InDesign.
The document discusses key concepts in digital graphics and design including:
- The differences between raster (bitmap) and vector graphics and their uses.
- Anti-aliasing techniques to reduce jagged edges in raster images.
- Factors that impact image quality such as resolution, aspect ratio, and file formats.
- Color models like RGB and CMYK.
- Popular design software like Adobe Photoshop, Illustrator, and InDesign.
This document discusses key concepts in digital image production including raster images, vector images, anti-aliasing, and resolution. Raster images are made of pixels and can look pixelated when zoomed in, while vector images use mathematical equations to scale smoothly without pixilation. Anti-aliasing minimizes aliasing artifacts by smoothing jagged pixel edges. Resolution refers to the number of pixels per inch, with higher resolution images containing more detail.
The document provides information about various types of digital image formats including raster images, vector images, and file formats. It discusses key aspects of raster images such as how they represent images using pixels that store color data. It contrasts raster images with vector images which use geometric primitives and mathematical equations. It also briefly outlines some common file formats and color models used in digital images.
This document provides information on various topics related to digital images and design software. It discusses the differences between raster and vector images, describes anti-aliasing and its purpose, and covers concepts like resolution, aspect ratio, and file formats. Color models like RGB and CMYK are explained as well as design programs like Photoshop, Illustrator, and InDesign. Sources are provided for further reading on each topic.
The document discusses various topics related to digital images, including raster images, vector images, file formats, color models, and image editing software. Raster images represent images as a grid of pixels while vector images use geometric primitives. Common file formats include JPEG, TIFF, EPS, PSD, and PDF. Color models include RGB, CMYK, and HSV/HSL. Adobe Photoshop and Illustrator are widely used image editing programs.
This document provides technical information on various features of Adobe InDesign, including:
- Text settings for laying out Arabic, Hebrew and other right-to-left languages.
- Bi-directional text flow allowing mixing of right-to-left and left-to-right paragraphs and stories.
- Automatic table of contents generation in multiple languages.
- Index creation and sorting options according to language.
- Import and export capabilities including QuarkXPress file conversion and various image formats.
- A reverse layout feature for converting between left-to-right and right-to-left documents.
This is the subject slides for the module MMS2401 - Multimedia System and Communication taught in Shepherd College of Media Technology, Affiliated with Purbanchal University.
This document discusses key concepts in digital graphics and design including:
Vector graphics use mathematical equations to represent images while raster graphics use a grid of pixels. Anti-aliasing tricks the eye into perceiving jagged edges as smooth.
File formats like JPEG, GIF, TIFF, EPS, PSD, and PDF are used to encode images for storage with different formats suited to different types of images.
Color models also differ between RGB used for computer displays and CMYK used for printed materials.
Adobe Photoshop, Illustrator, and InDesign are prominent design software, with Photoshop allowing image editing and the others specialized for vector graphics and page layout respectively.
Vectors are based on geometric elements like points, lines, and shapes defined by mathematical expressions. They represent images using control points on the x and y axes. Properties like color and thickness don't increase file size.
Bitmaps map domains like pixels to binary values of 0 or 1, representing black and white images. Pixmaps store more colors using more bits per pixel.
Digital cameras and scanners capture images digitally which are then processed into formats like JPEGs of various sizes for web or full screen display. Factors like lens quality, focus, noise, and dynamic range impact image quality.
Image file formats use vector data, pixels, or mixtures to store and organize graphics. File size increases
Wondering about using PNG or JPG or BMP or GIF. This presentation will answer all your queries related to designing digital images and which formats are best while saving them..
Terms like raster images, vector images, vectors, alpha channels, transparency, palettes, compression are explained here.
Raster graphics store images as a grid of pixels that can lose detail when enlarged. Vector graphics use mathematical equations to define shapes, keeping images smooth at any size. Lossy compression discards some image data, resulting in loss of pixels and detail, while lossless compression reduces file size by about 50% without data loss. File formats like BMP, PNG, GIF, TIFF, JPG, and PSD are used for different types of images and uses.
This document discusses image processing and summarizes several key techniques. It begins by defining image processing and describing how images are digitized and processed. It then summarizes three main categories of image processing: image enhancement, image restoration, and image compression. Specific techniques discussed include contrast stretching, density slicing, and edge enhancement. The document also discusses visual saliency models, motion saliency, and using conditional random fields for video object extraction.
Voice recognition and voice response systems allow for hands-free data entry using speech as the interface. Voice recognition systems analyze speech patterns to convert them to digital codes for computer input. Most require training a system to recognize a user's voice. Voice recognition is used in applications like manufacturing quality control and airline baggage sorting. Voice response systems provide verbal guidance for tasks using voice messaging and synthesis. Examples include automated phone systems and online services.
This technical file discusses various concepts related to digital images, including vector graphics, raster images, anti-aliasing, resolution, aspect ratio, file formats, color models, and image editing software such as Adobe Photoshop, Illustrator, and InDesign. Vector graphics use mathematical equations to represent images while raster images use a grid of pixels. Anti-aliasing makes rough edges appear smoother. Resolution and aspect ratio affect image quality and size. Different file formats are used to save images. Color models describe how colors are represented numerically. Photoshop, Illustrator, and InDesign allow for digital image manipulation and design.
This document provides information on various graphics and design topics including raster graphics, vector graphics, antialiasing, resolution, aspect ratio, file formats, color models, and Adobe software like Photoshop, Illustrator, and InDesign. Raster graphics use pixels to form images while vector graphics use mathematical formulas. Photoshop is used for photo editing, Illustrator for vector graphics and design work, and InDesign for print layouts like magazines.
The document describes creating a label for a campaign focusing on a question rather than a statement. The label features a picture of a person resembling Superman holding a tablet with a question mark, representing their uncertainty about taking the tablets. To create the label, the image was filtered to have a sketch-like effect and text was added. This label was the easiest to create as the tablets were already in the hand in the original photo.
The artist created a mirrored image of a girl from "The Brook" by highlighting her figure, copying it to the other side, and removing parts of the background. This final image conceptually represents one side of the girl unsure of what to do and the other side having a new idea, reflecting The Brook's role in helping people make decisions.
This document describes the first image the author manipulated in Photoshop. They removed the background to focus only on the picture and text. They increased the contrast and brightness to make the face and background stand out from each other. The manipulated image was intended to depict depression for a mental health organization by showing a down expression with uplifting text.
The document discusses three fantasy films: Lord of the Rings: The Two Towers, Star Wars: A New Hope, and Pirates of the Caribbean: The Curse of the Black Pearl. It provides synopses of the plots for each film. It also discusses what attracts the author to the fantasy genre, including actors, stories, and special effects. Finally, it discusses several film theory concepts used in fantasy films, such as intertextuality, star theory, and reception theory.
Henry Cavill is praised as the new Superman but the author doubts his ability for such a large role. Scarlett Johansson's work is inspiring and she was great in Iron Man and The Avengers. The Thing is summarized as a horror/sci-fi film about an alien discovered at an Antarctic research site that escapes and causes conflict. Star power, like Seth Rogen's likable roles, contributed to 50/50's success over The Thing despite the latter earning more initially due to better marketing.
1) Captain America is about a man who is deemed unfit for the military but volunteers for an experiment that turns him into Captain America and gives him superhero abilities, which he uses to defend American values.
2) The film was marketed through TV ads, websites, Facebook groups, YouTube trailers, billboards, newspaper reviews and interviews to target audiences of males ages 16-24 and 25+, as well as more females by using an attractive lead actor and including romance.
3) Merchandise like action figures, posters, games and comics were used to appeal to fans of superheroes and drive synergies.
James Fox conducted research on magazine layout and house style by distributing questionnaires and researching magazine designs. He analyzed various magazine cover and content page designs to understand differences and how to design his own magazine. The house style he chose was Kozuka Mincho, which he felt had a catchy ring to it and worked well with the "Sharpy but Smarty" layout of his magazine. He created basic and more advanced designs for the cover, contents page, and double page spread to enhance the house style and add more design elements. To obtain feedback, he created a questionnaire and calculated the results.
This document compares the designs of DETAILS and Men's VOGUE magazines. DETAILS focuses on men's health and fashion, using celebrities like Robert Pattinson to promote the magazine. It displays the issue number and cover lines prominently. Men's VOGUE focuses on advertising brands and celebrities to showcase wealth and desires, and informs readers of the latest worldwide fashion trends, promoting James Franco as the new James Dean. The document also analyzes the cover lines used by Men's VOGUE to advertise fashion, producers, exclusive content, features, and additional information.
This document discusses different applications of photography across several industries:
- Advertising photography is key for attracting viewers' attention in advertising campaigns through compelling images.
- Fashion photographer Patrick Demarchelier's work is widely advertised and he was the official photographer for Princess Diana.
- Music photographer Kevin Cummins is known for his photos of bands like The Rolling Stones and Morrissey.
- Sports photographer Bill Frakes has worked for Sports Illustrated since 1993.
- Photojournalism uses images to tell news stories in an impartial, factual way.
- Fine art photography expresses the artist's subjective vision rather than just documenting reality.
This document contains two front cover layout designs. The first is a basic design intended to help enhance house style and cover elements. The second is a more advanced final project cover that builds upon the first by adding additional elements like cover lines, subject titles, and promotional text.
This document contains two contents pages that were designed by the author to improve their house style, imagery, and layout skills. The first page is a basic layout that was created to enhance these factors. The second page is more advanced and was produced for a final major project, building upon the first page by further enhancing the similarities and adding more design elements.
This document appears to be a survey containing multiple choice questions about magazine preferences. It asks respondents about their gender, age, favorite magazine, how much they would pay for a magazine, what their favorite part of a magazine is, if they read reviews, if they would change anything about magazines, if they watch magazine features, if they would buy a magazine if it was published weekly, if they read online magazines or blogs, and if they would change anything about online magazines. The questions cover topics like demographics, interests, spending habits, and preferences regarding print versus online content.
The document analyzes the front covers of DETAILS and Men's VOGUE magazines. DETAILS focuses on men's health and fashion, using celebrities like Robert Pattinson to promote the magazine. It uses large font and cover lines to advertise the main stories, including a feature on Pattinson. Men's VOGUE focuses on advertising brands and celebrities to showcase wealth and fashion trends. Its cover promotes an article comparing James Franco to James Dean. Both magazines effectively use cover design and lines to promote their content.
Harrison Reed Delve, founder of Delve's Fashion, was interviewed for Unique Magazine about his background, interests, and work in the fashion industry. Delve grew up in London and overcame a difficult childhood to study fashion design. He discussed favorite designers and models he's worked with, as well as the importance of perfection and popularity in his work. Readers are invited to learn more about Delve and his upcoming fashion shows on his website or by visiting an event in London in August.
The document discusses editing images in Adobe Photoshop. Specifically, it mentions using the Rectangular Marquee tool to select an area of an image, applying a grayscale effect to give the image an old but shiny look, and saving the edited image as a JPEG to avoid complications when importing it elsewhere.
The document describes editing images in Photoshop. The author selected an area of an image using the Rectangular Marquee tool, applied a grayscale effect to the selection, and saved the edited image as a Jpeg file to avoid complications when importing it elsewhere.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
3. BTec Level 3
Extended Diploma in Creative Media Production
HA1 - Technical File – James Fox
4. BTec Level 3
Extended Diploma in Creative Media Production
HA1 - Technical File – Raster Images
In computer graphics, a raster graphics image, or bitmap,
is a data structure representing a generally rectangular grid
of pixels, or points of colour, viewable via a monitor, paper,
or other display medium. Raster images are stored in
image files with varying formats (see Comparison of
graphics file formats).
A bitmap corresponds bit-for-bit with an image displayed
on a screen, generally in the same format used for storage
in the display's video memory, or maybe as a device-
independent bitmap. A bitmap is technically characterized
by the width and height of the image in pixels and by the
number of bits per pixel (a colour depth, which determines
the number of colours it can represent).
5. BTec Level 3
Extended Diploma in Creative Media Production
HA1 - Technical File – Vector Images Vector graphics is the use of geometrical
primitives such as points, lines, curves, and
shapes or polygon(s), which are all based on
mathematical equations, to represent images
in computer graphics.
Vector graphics formats are complementary
to raster graphics, which is the
representation of images as an array of pixels,
as is typically used for the representation of
photographic images. Vector graphics are
stored as mathematical expressions as
opposed to bit mapped graphics which are
stored as a series of mapped 'dots', also
known as pixels (Picture cells).
There are instances when working with
vector tools and formats is the best practice,
and instances when working with raster tools
and formats is the best practice. There are
times when both formats come together. An
understanding of the advantages and
limitations of each technology and the
relationship between them is most likely to
result in efficient and effective use of tools.
6. BTec Level 3
Extended Diploma in Creative Media Production
In digital signal processing, spatial anti-aliasing is
the technique of minimizing the distortion artefacts
known as aliasing when representing a high-
resolution image at a lower resolution. Anti-aliasing
is used in digital photography, computer graphics,
digital audio, and many other applications.
Anti-aliasing means removing signal components
that have a higher frequency than is able to be
properly resolved by the recording (or sampling)
device. This removal is done before (re)sampling at
a lower resolution. When sampling is performed
without removing this part of the signal, it causes
undesirable artefacts such as the black-and-white
noise near the top of figure 1-a below.
In signal acquisition and audio, anti-aliasing is often
done using an analogy anti-aliasing filter to remove
the out-of-band component of the input signal prior
to sampling with an analogy-to-digital converter. In
digital photography, optical anti-aliasing filters are
made of birefringent materials, and smooth the
signal in the spatial optical domain. The anti-
aliasing filter essentially blurs the image slightly in
order to reduce resolution to below the limit of the
digital sensor (the larger the pixel pitch, the lower
the achievable resolution at the sensor level).
7. BTec Level 3
Extended Diploma in Creative Media Production
In digital audio, bit depth describes the
number of bits of information recorded
for each sample. Bit depth directly
corresponds to the resolution of each
sample in a set of digital audio data.
Common examples of bit depth include
CD quality audio, which is recorded at 16
bits, and DVD-Audio, which can support
up to 24-bit audio.
A set of digital audio samples contains
data that, when converted into an analogy
signal, provides the necessary
information to reproduce the sound
wave. In pulse-code modulation (PCM)
sampling, the bit depth will limit signal-to-
noise ratio (S/N). The bit depth will not
limit frequency range, which is limited by
the sample rate.
8. BTec Level 3
Extended Diploma in Creative Media Production
The aspect ratio of a shape is the ratio of
its longer dimension to its shorter
dimension. It may be applied to two
characteristic dimensions of a three-
dimensional shape, such as the ratio of the
longest and shortest axis, or for
symmetrical objects that are described by
just two measurements, such as the length
and diameter of a rod. The aspect ratio of a
torus is the ratio of the major axis R to the
minor axis r.
9. BTec Level 3
Extended Diploma in Creative Media Production
A file format is a particular way that information is
encoded for storage in a computer file. Portable
Document Format (PDF) is a file format used to represent
documents in a manner independent of application
software, hardware, and operating systems Each PDF file
encapsulates a complete description of a fixed-layout flat
document, including the text, fonts, graphics, and other
information needed to display it. In computing, JPEG is a
commonly used method of lousy compression for digital
photography (image). The degree of compression can be
adjusted, allowing a selectable tradeoffs between storage
size and image quality. JPEG typically achieves 10:1
compression with little perceptible loss in image quality.
The Graphics Interchange Format (GIF The format
supports up to 8 bits per pixel thus allowing a single image
to reference a palette of up to 256 distinct colours. The
colours are chosen from the 24-bit RGB colour space. It
also supports animations and allows a separate palette of
256 colours for each frame. TIFF (originally standing for
Tagged Image File Format) is a file format for storing
images, popular among graphic artists, the publishing
industry, and both amateur and professional
photographers in general. PSD (Photoshop document),
the default file extension of the proprietary file format of
Adobe System's Photoshop program.
A portable or personal storage device, small hard disks
designed to copy digital photographs from a camera.
10. BTec Level 3
Extended Diploma in Creative Media Production
A color model is an abstract mathematical model
describing the way colours can be represented as tuples of
numbers, typically as three or four values or color
components. When this model is associated with a precise
description of how the components are to be interpreted
(viewing conditions, etc.), the resulting set of colors is
called color space. This section describes ways in which
human color vision can be modeled. There are various
types of color systems that classify color and analyse their
effects. The American Munsell color system devised by
Albert H. Munsell is a famous classification that organises
various colors into a color solid based on hue, saturation
and value. Other important color systems include the
Swedish Natural Color System (NCS) from the
Scandinavian Color Institute, the Optical Society of
America's Uniform Color Space (OSA-UCS), and the
Hungarian Coloroid system developed by Antal Nemcsics
from the Budapest University of Technology and
Economics. Of those, the NCS is based on the opponent-
process color model, while the Munsell, the OSA-UCS and
the Coloroid attempt to model color uniformity. The
American Pantone and the German RAL commercial
color-matching systems differ from the previous ones in
that their color spaces are not based on an underlying
color model.
11. BTec Level 3
Extended Diploma in Creative Media Production
Adobe Photoshop is a graphics editing program
developed and published by Adobe Systems
Incorporated.
Adobe's 2003 "Creative Suite" rebranding led to
Adobe Photoshop 8's renaming to Adobe
Photoshop CS. Thus, Adobe Photoshop CS5 is
the 12th major release of Adobe Photoshop. The
CS rebranding also resulted in Adobe offering
numerous software packages containing multiple
Adobe programs for a reduced price. Adobe
Photoshop is released in two editions: Adobe
Photoshop, and Adobe Photoshop Extended,
with the Extended having extra 3D image
creation, motion graphics editing, and advanced
image analysis features. Adobe Photoshop
Extended is included in all of Adobe's Creative
Suite offerings except Design Standard, which
includes the Adobe Photoshop edition.
12. BTec Level 3
Extended Diploma in Creative Media Production
Adobe Illustrator is a vector graphics editor
developed and marketed by Adobe Systems.
Illustrator is similar in scope, intended market,
and functionality to its competitors, CorelDraw
and Macromedia FreeHand. Starting with version
1.0, Adobe chose to license an image of Sadra
Botticelli's "The Birth of Venus" from the
Bettmann Archive and use the portion containing
Venus' face as Illustrator's branding image.
Warnock desired a Renaissance image to evoke
his vision of Postscript as a new Renaissance in
publishing, and Adobe employee Luanne
Seymour Cohen, who was responsible for the
early marketing material, found Venus' flowing
tresses a perfect vehicle for demonstrating
Illustrator's strength in tracing smooth curves
over bitmap source images. Over the years the
rendition of this image on Illustrator's splash
screen and packaging became more stylized to
reflect features added in each version.
13. BTec Level 3
Extended Diploma in Creative Media Production
Adobe In Design is a software application
produced by Adobe Systems. It can be used to
create works such as posters, flyers, brochures,
magazines, newspapers and books. In
conjunction with Adobe Digital Publishing Suite
In designing can publish content suitable for
tablet devices. Graphic designers and
production artists are the principal users,
creating and laying out periodical publications,
posters, and print media. It also supports export
to EPUB and SWF formats to create digital
publications, and content suitable for
consumption on tablet computer devices. The
Adobe In Copy word processor uses the same
formatting engine as In Design.