1) Phase unwrapping is used in optical quadrature microscopy to determine viability of embryos by counting cells after unwrapping. It needs to be done at near real-time speeds to analyze sample changes.
2) The paper implements minimum LP norm phase unwrapping and affine transformations on a GPU to improve performance and latency for optical microscopy research.
3) Performance results show a 5.24x speedup for total phase unwrapping time compared to a serial CPU implementation. Further optimizations like multi-GPU support could improve speeds for higher image acquisition rates.
A Noncausal Linear Prediction Based Switching Median Filter for the Removal o...IDES Editor
In this paper, we propose a switching based median
filter for the removal of impulse noise, namely, the salt and
pepper noise in gray scale images. The filter is based on the
concept of substitution of noisy pixels prior to estimation. It
effectively suppresses the impulse noise in two stages. First,
the noisy pixels are detected by using the signal dependent
rank-ordered mean (SD-ROM) filter. In the second stage, the
noisy pixels are first substituted by the first order 2D
noncausal linear prediction technique and subsequently
replaced by the median value. Extensive simulations are
carried out to validate the proposed method. Experimental
results show improvements both visually and quantitatively
compared to other switching based median filters for the
removal of salt-and-pepper noise at different densities.
The optical constants of highly absorbing films using the spectral reflectanc...Alexander Decker
The document summarizes a method for determining the optical constants (refractive index and extinction coefficient) of highly absorbing thin films using only spectral reflectance measurements. It describes using Kramers-Kronig relations to calculate the phase angle from reflectance data, and then determining the real refractive index and extinction coefficient. The method is applied to rhodium films of different thicknesses, and the calculated optical constants are found to agree to within 5% of literature values and those from an interference-based method.
Abstract: Noise in an image is a serious problem In this
project, the various noise conditions are studied which are:
Additive white Gaussian noise (AWGN), Bipolar fixedvalued impulse noise, also called salt and pepper noise
(SPN), Random-valued impulse noise (RVIN), Mixed noise
(MN). Digital images are often corrupted by impulse noise
during the acquisition or transmission through
communication channels the developed filters are meant for
online and real-time applications. In this paper, the
following activities are taken up to draw the results: Study
of various impulse noise types and their effect on digital
images; Study and implementation of various efficient
nonlinear digital image filters available in the literature
and their relative performance comparison;
This document discusses data analysis techniques for refraction tomography including data conversion, signal killing, picking approaches, and model geometry. It provides instructions on installing picking software, naming converted data files sequentially, fixing header sizes, deleting unwanted traces based on component, and approaches for manual and automated first break picking. Examples of clear seismic records that make first arrival picking easy are also shown.
Presentación de la Universidad de Granada sobre cambios de color en escenarios naturales debidos a la interacción entre luz y atmósfera, realizada durante las jornadas HOIP 2010 organizadas por la Unidad de Sistemas de Información e Interacción TECNALIA.
Más información en http://www.tecnalia.com/es/ict-european-software-institute/index.htm
This document discusses representation in low-level visual learning. It summarizes that most visual learning has used overly simplified models and representation matters. It then reviews several approaches for tasks like image segmentation, optical flow estimation, and motion modeling that use more sophisticated representations like Markov random fields, probabilistic graphical models, and layered models that explicitly model occlusion. The document argues these approaches that incorporate spatial context and multi-scale representations have achieved better performance than early simplified models on tasks like image segmentation, optical flow estimation, and motion modeling.
A Noncausal Linear Prediction Based Switching Median Filter for the Removal o...IDES Editor
In this paper, we propose a switching based median
filter for the removal of impulse noise, namely, the salt and
pepper noise in gray scale images. The filter is based on the
concept of substitution of noisy pixels prior to estimation. It
effectively suppresses the impulse noise in two stages. First,
the noisy pixels are detected by using the signal dependent
rank-ordered mean (SD-ROM) filter. In the second stage, the
noisy pixels are first substituted by the first order 2D
noncausal linear prediction technique and subsequently
replaced by the median value. Extensive simulations are
carried out to validate the proposed method. Experimental
results show improvements both visually and quantitatively
compared to other switching based median filters for the
removal of salt-and-pepper noise at different densities.
The optical constants of highly absorbing films using the spectral reflectanc...Alexander Decker
The document summarizes a method for determining the optical constants (refractive index and extinction coefficient) of highly absorbing thin films using only spectral reflectance measurements. It describes using Kramers-Kronig relations to calculate the phase angle from reflectance data, and then determining the real refractive index and extinction coefficient. The method is applied to rhodium films of different thicknesses, and the calculated optical constants are found to agree to within 5% of literature values and those from an interference-based method.
Abstract: Noise in an image is a serious problem In this
project, the various noise conditions are studied which are:
Additive white Gaussian noise (AWGN), Bipolar fixedvalued impulse noise, also called salt and pepper noise
(SPN), Random-valued impulse noise (RVIN), Mixed noise
(MN). Digital images are often corrupted by impulse noise
during the acquisition or transmission through
communication channels the developed filters are meant for
online and real-time applications. In this paper, the
following activities are taken up to draw the results: Study
of various impulse noise types and their effect on digital
images; Study and implementation of various efficient
nonlinear digital image filters available in the literature
and their relative performance comparison;
This document discusses data analysis techniques for refraction tomography including data conversion, signal killing, picking approaches, and model geometry. It provides instructions on installing picking software, naming converted data files sequentially, fixing header sizes, deleting unwanted traces based on component, and approaches for manual and automated first break picking. Examples of clear seismic records that make first arrival picking easy are also shown.
Presentación de la Universidad de Granada sobre cambios de color en escenarios naturales debidos a la interacción entre luz y atmósfera, realizada durante las jornadas HOIP 2010 organizadas por la Unidad de Sistemas de Información e Interacción TECNALIA.
Más información en http://www.tecnalia.com/es/ict-european-software-institute/index.htm
This document discusses representation in low-level visual learning. It summarizes that most visual learning has used overly simplified models and representation matters. It then reviews several approaches for tasks like image segmentation, optical flow estimation, and motion modeling that use more sophisticated representations like Markov random fields, probabilistic graphical models, and layered models that explicitly model occlusion. The document argues these approaches that incorporate spatial context and multi-scale representations have achieved better performance than early simplified models on tasks like image segmentation, optical flow estimation, and motion modeling.
This document discusses a technique for removing impulse noise from digital images using image fusion. It first filters a noisy input image using five different smoothing filters: median filter, vector median filter (VMF), basic vector directional filter (BVDF), switched median filter (SMF), and modified switched median filter (MSMF). The filtered images are then fused to obtain a single denoised output image with better quality than the individually filtered images. Edge detection is performed on the fused image using Canny filter to evaluate the noise cancellation performance from a human perception perspective. Experimental results show the proposed fusion technique produces better results compared to filtering with a single algorithm.
This document presents a summary of a research paper on shape from focus. Shape from focus is a technique that uses differences in focus levels across a series of images to obtain depth information and reconstruct the 3D shape of an object. The paper develops a sum-modified Laplacian (SML) operator to provide local measures of image focus quality. The SML operator is applied to images captured at different focus levels to determine focus measures. A depth estimation algorithm then interpolates the focus measures to obtain accurate depth estimates for each point. Results show the SML operator provides robust focus measures and the overall shape from focus approach can effectively reconstruct shapes, making it suitable for challenging visual inspection problems.
This document summarizes a research paper that proposes a new method for reducing noise in digital images using curvelet transformation with Log Gabor filtering. It begins by introducing common sources of noise in digital images and existing denoising methods. It then describes curvelet transformation and Log Gabor filtering in more detail. The proposed method decomposes a noisy image into wavelets, applies curvelet transformation with Log Gabor filtering to attenuate color frequencies, and then reconstructs the image. The document presents this methodology and compares the denoised image quality to other methods using peak signal-to-noise ratio (PSNR). Experimental results showed that the proposed curvelet transformation with Log Gabor filtering produces higher PSNR values and less visual artifacts
SAL3D presentation - AQSENSE's 3D machine vision libraryAQSENSE S.L.
The 3D Shape Analysis Library (http://www.aqsense.com/products/sal3d) is the first hardware independent software architecture for range map and poing cloud processing, fully oriented to laser triangulation and 3D machine vision applications.
SAL3D means speed, accuracy, and reliability to machine builders, equipment manufacturers, system integrators, and volume end users demanding maximum flexibility and customization in their vision systems. Tools can be integrated as DLL's that allow developers access to third party components usable side by side with SAL's tools resulting in rapid development of highly complex processing tasks.
1989 optical measurement of the refractive index, layer thickness, and volume...pmloscholte
This document discusses a method for determining the complex refractive index, layer thickness, and volume changes of thin films using optical measurements. The method involves measuring reflectance and transmittance values across a range of intentionally varied layer thicknesses, rather than fitting those values as functions of independently measured thicknesses. The measurements provide information needed for optical recording applications. The complex refractive index, layer thicknesses, and volume changes can then be unambiguously calculated by fitting curves to the reflectance-transmittance plane measured across multiple thicknesses. An example application determines these properties for thin films of GaSb and InSb for use in optical recording.
This document summarizes and compares local image descriptors. It begins with an introduction to modern descriptors like SIFT, SURF and DAISY. It then discusses efficient descriptors such as binary descriptors like BRIEF, ORB and BRISK which use comparisons of intensity value pairs. The document concludes with an overview section.
Ph.D. Thesis Presentation: A Study of Priors and Algorithms for Signal Recove...Shunsuke Ono
This document summarizes a dissertation on developing new priors and algorithms for signal recovery problems solved via convex optimization. Chapter 4 proposes a blockwise low-rank prior called the Block Nuclear Norm (BNN) to better model texture patterns in images. BNN represents textures as locally low-rank blocks under different shears. Chapter 5 introduces the Local Color Nuclear Norm (LCNN) prior to promote the color-line property and reduce color artifacts in restored images. Chapter 6 develops a hierarchical convex optimization algorithm using primal-dual splitting to solve problems with non-unique solutions and non-strictly convex objectives.
Fast Structure From Motion in Planar Image SequencesLuigi Bagnato
1. The document proposes a fast structure from motion method for planar image sequences based on parallel projection and optical flow.
2. It formulates the problem using a brightness consistency equation relating pixel intensities in successive images under parallel projection.
3. Depth is estimated by solving an optimization problem that minimizes total variation of the depth map while maximizing photo-consistency between optical flow warped images, formulated in the discrete domain.
Random Valued Impulse Noise Removal in Colour Images using Adaptive Threshold...IDES Editor
To remove random valued impulse noise from
colour images, an efficient impulse detection and filtering
scheme is presented. The locally adaptive threshold for
impulse detection is derived from the pixels of the filtering
window. The restoration of the noisy pixel is done on the basis
of brightness and chromaticity information obtained from the
neighbouring pixels in the filtering window. Experimental
results demonstrate that the proposed scheme yields much
superior performance in comparison with other colour image
filtering methods.
The document discusses analyzing the brightness variation of the SX Phoenicis variable star XX Cyg using differential photometry on images taken with different optical filters. It outlines the background on variable stars, the author's senior thesis project to determine XX Cyg's period using brightness data from V and R filter images, and the theory that SX Phoenicis stars pulsate radially and nonradially. The methods section describes the telescope and camera used to acquire data, and the process of calibration, aperture photometry, and determining the period from the brightness information.
Applications for high speed Raman Microscopynweavers
The RAMAN-11 is a new generation of laser Raman microscope developed by Nanophoton that enables the fastest high definition Raman imaging. It combines laser microscope and Raman spectroscopy technologies. The RAMAN-11's imaging speed is 300-600 times faster than competitors and it opens up new applications. Its software supports rapid data acquisition and robust analysis functions.
Exploring Methods to Improve Edge Detection with Canny AlgorithmPrasad Thakur
This document explores methods to improve edge detection using the Canny algorithm. It first discusses edge detection and problems with standard methods. It then surveys literature on modern non-Canny and Canny-based approaches. Three methods are explored: a recursive method that applies Canny to sub-images, edge filtering using conditional probability, and edge linking. Results show the recursive method preserves edges better at smaller scales while edge filtering and linking refine edges but depend on Canny output. Analysis finds optimal parameters are a block size of 32, kernel size of 5, and probability threshold of 0.6.
This document discusses various feature detectors used in computer vision. It begins by describing classic detectors such as the Harris detector and Hessian detector that search scale space to find distinguished locations. It then discusses detecting features at multiple scales using the Laplacian of Gaussian and determinant of Hessian. The document also covers affine covariant detectors such as maximally stable extremal regions and affine shape adaptation. It discusses approaches for speeding up detection using approximations like those in SURF and learning to emulate detectors. Finally, it outlines new developments in feature detection.
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.
study Image and video abstraction by multi scale anisotropic kuwaharaChiamin Hsu
The document describes a multi-scale anisotropic Kuwahara filter for image abstraction and edge-preserving smoothing. It proposes a coarse-to-fine approach using an image pyramid. At each level, it applies an anisotropic Kuwahara filter using locally estimated structure tensors to determine filter shapes, and merges the results with the previous level. This avoids artifacts and overblurring seen in other filters, producing strong abstraction while preserving details in low-contrast regions.
Land Cover Feature Extraction using Hybrid Swarm Intelligence Techniques - A ...IDES Editor
This document presents a hybrid algorithm using biogeography-based optimization (BBO) and ant colony optimization (ACO) for land cover feature extraction from remote sensing images. The algorithm first analyzes a training image to identify features that BBO and ACO classify efficiently. It then applies BBO to clusters containing these features and ACO to remaining clusters. An evaluation shows the hybrid algorithm achieves a higher kappa coefficient of 0.97 compared to 0.67 for BBO alone, indicating better classification accuracy. The authors conclude the algorithm effectively handles uncertainties in remote sensing images and future work could improve efficiency further.
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 summarizes a method for acquiring stereo image pairs with pixel-accurate ground truth correspondence information using structured light. The method involves projecting patterns of structured light onto a scene using one or more light projectors while capturing images using a pair of cameras. By decoding the projected light patterns, each pixel can be uniquely labeled, allowing trivial determination of correspondences between camera views. The structured light patterns help overcome limitations of existing stereo datasets in evaluating stereo matching algorithms.
1) Robust wavelet denoising is proposed as an improvement over traditional waveshrink and basis pursuit methods, which are less effective when noise is non-Gaussian and contains outliers.
2) The proposed method formulates robust wavelet denoising as an optimization problem that minimizes a robust loss function, such as the Huber loss function, rather than least squares.
3) Two algorithms are proposed to solve the robust wavelet denoising optimization problem: block coordinate relaxation and an interior point method. Parameter selection is also discussed.
Image Splicing Detection involving Moment-based Feature Extraction and Classi...IDES Editor
In the modern age, the digital image has taken
the place of the original analog photograph, and the forgery
of digital images has become increasingly easy, and harder
to detect. Image splicing is the process of making a
composite picture by cutting and joining two or more
photographs. An approach to efficient image splicing
detection is proposed here. The spliced image often
introduces a number of sharp transitions such as lines,
edges and corners. Phase congruency is a sensitive measure
of these sharp transitions and is hence proposed as a
feature for splicing detection. Statistical moments of
characteristic functions of wavelet sub-bands have been
examined to detect the differences between the authentic
images and spliced images. Image splicing detection can be
treated as a two-class pattern recognition problem, which
builds the model using moment features and some other
parameters extracted from the given test image. Artificial
neural network (ANN) is chosen as a classifier to train and
test the given images.
The document proposes two algorithms for fingerprint classification based on singular point detection. The first algorithm uses directional images and masks to detect core and delta point neighborhoods, then analyzes histograms to locate exact singular points. The second algorithm detects neighborhoods based on curvature and direction changes, then uses Poincare index to identify candidate points. Both aim to classify fingerprints into arch, loop, or whorl categories based on identified singular point types and positions.
This document discusses a technique for removing impulse noise from digital images using image fusion. It first filters a noisy input image using five different smoothing filters: median filter, vector median filter (VMF), basic vector directional filter (BVDF), switched median filter (SMF), and modified switched median filter (MSMF). The filtered images are then fused to obtain a single denoised output image with better quality than the individually filtered images. Edge detection is performed on the fused image using Canny filter to evaluate the noise cancellation performance from a human perception perspective. Experimental results show the proposed fusion technique produces better results compared to filtering with a single algorithm.
This document presents a summary of a research paper on shape from focus. Shape from focus is a technique that uses differences in focus levels across a series of images to obtain depth information and reconstruct the 3D shape of an object. The paper develops a sum-modified Laplacian (SML) operator to provide local measures of image focus quality. The SML operator is applied to images captured at different focus levels to determine focus measures. A depth estimation algorithm then interpolates the focus measures to obtain accurate depth estimates for each point. Results show the SML operator provides robust focus measures and the overall shape from focus approach can effectively reconstruct shapes, making it suitable for challenging visual inspection problems.
This document summarizes a research paper that proposes a new method for reducing noise in digital images using curvelet transformation with Log Gabor filtering. It begins by introducing common sources of noise in digital images and existing denoising methods. It then describes curvelet transformation and Log Gabor filtering in more detail. The proposed method decomposes a noisy image into wavelets, applies curvelet transformation with Log Gabor filtering to attenuate color frequencies, and then reconstructs the image. The document presents this methodology and compares the denoised image quality to other methods using peak signal-to-noise ratio (PSNR). Experimental results showed that the proposed curvelet transformation with Log Gabor filtering produces higher PSNR values and less visual artifacts
SAL3D presentation - AQSENSE's 3D machine vision libraryAQSENSE S.L.
The 3D Shape Analysis Library (http://www.aqsense.com/products/sal3d) is the first hardware independent software architecture for range map and poing cloud processing, fully oriented to laser triangulation and 3D machine vision applications.
SAL3D means speed, accuracy, and reliability to machine builders, equipment manufacturers, system integrators, and volume end users demanding maximum flexibility and customization in their vision systems. Tools can be integrated as DLL's that allow developers access to third party components usable side by side with SAL's tools resulting in rapid development of highly complex processing tasks.
1989 optical measurement of the refractive index, layer thickness, and volume...pmloscholte
This document discusses a method for determining the complex refractive index, layer thickness, and volume changes of thin films using optical measurements. The method involves measuring reflectance and transmittance values across a range of intentionally varied layer thicknesses, rather than fitting those values as functions of independently measured thicknesses. The measurements provide information needed for optical recording applications. The complex refractive index, layer thicknesses, and volume changes can then be unambiguously calculated by fitting curves to the reflectance-transmittance plane measured across multiple thicknesses. An example application determines these properties for thin films of GaSb and InSb for use in optical recording.
This document summarizes and compares local image descriptors. It begins with an introduction to modern descriptors like SIFT, SURF and DAISY. It then discusses efficient descriptors such as binary descriptors like BRIEF, ORB and BRISK which use comparisons of intensity value pairs. The document concludes with an overview section.
Ph.D. Thesis Presentation: A Study of Priors and Algorithms for Signal Recove...Shunsuke Ono
This document summarizes a dissertation on developing new priors and algorithms for signal recovery problems solved via convex optimization. Chapter 4 proposes a blockwise low-rank prior called the Block Nuclear Norm (BNN) to better model texture patterns in images. BNN represents textures as locally low-rank blocks under different shears. Chapter 5 introduces the Local Color Nuclear Norm (LCNN) prior to promote the color-line property and reduce color artifacts in restored images. Chapter 6 develops a hierarchical convex optimization algorithm using primal-dual splitting to solve problems with non-unique solutions and non-strictly convex objectives.
Fast Structure From Motion in Planar Image SequencesLuigi Bagnato
1. The document proposes a fast structure from motion method for planar image sequences based on parallel projection and optical flow.
2. It formulates the problem using a brightness consistency equation relating pixel intensities in successive images under parallel projection.
3. Depth is estimated by solving an optimization problem that minimizes total variation of the depth map while maximizing photo-consistency between optical flow warped images, formulated in the discrete domain.
Random Valued Impulse Noise Removal in Colour Images using Adaptive Threshold...IDES Editor
To remove random valued impulse noise from
colour images, an efficient impulse detection and filtering
scheme is presented. The locally adaptive threshold for
impulse detection is derived from the pixels of the filtering
window. The restoration of the noisy pixel is done on the basis
of brightness and chromaticity information obtained from the
neighbouring pixels in the filtering window. Experimental
results demonstrate that the proposed scheme yields much
superior performance in comparison with other colour image
filtering methods.
The document discusses analyzing the brightness variation of the SX Phoenicis variable star XX Cyg using differential photometry on images taken with different optical filters. It outlines the background on variable stars, the author's senior thesis project to determine XX Cyg's period using brightness data from V and R filter images, and the theory that SX Phoenicis stars pulsate radially and nonradially. The methods section describes the telescope and camera used to acquire data, and the process of calibration, aperture photometry, and determining the period from the brightness information.
Applications for high speed Raman Microscopynweavers
The RAMAN-11 is a new generation of laser Raman microscope developed by Nanophoton that enables the fastest high definition Raman imaging. It combines laser microscope and Raman spectroscopy technologies. The RAMAN-11's imaging speed is 300-600 times faster than competitors and it opens up new applications. Its software supports rapid data acquisition and robust analysis functions.
Exploring Methods to Improve Edge Detection with Canny AlgorithmPrasad Thakur
This document explores methods to improve edge detection using the Canny algorithm. It first discusses edge detection and problems with standard methods. It then surveys literature on modern non-Canny and Canny-based approaches. Three methods are explored: a recursive method that applies Canny to sub-images, edge filtering using conditional probability, and edge linking. Results show the recursive method preserves edges better at smaller scales while edge filtering and linking refine edges but depend on Canny output. Analysis finds optimal parameters are a block size of 32, kernel size of 5, and probability threshold of 0.6.
This document discusses various feature detectors used in computer vision. It begins by describing classic detectors such as the Harris detector and Hessian detector that search scale space to find distinguished locations. It then discusses detecting features at multiple scales using the Laplacian of Gaussian and determinant of Hessian. The document also covers affine covariant detectors such as maximally stable extremal regions and affine shape adaptation. It discusses approaches for speeding up detection using approximations like those in SURF and learning to emulate detectors. Finally, it outlines new developments in feature detection.
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.
study Image and video abstraction by multi scale anisotropic kuwaharaChiamin Hsu
The document describes a multi-scale anisotropic Kuwahara filter for image abstraction and edge-preserving smoothing. It proposes a coarse-to-fine approach using an image pyramid. At each level, it applies an anisotropic Kuwahara filter using locally estimated structure tensors to determine filter shapes, and merges the results with the previous level. This avoids artifacts and overblurring seen in other filters, producing strong abstraction while preserving details in low-contrast regions.
Land Cover Feature Extraction using Hybrid Swarm Intelligence Techniques - A ...IDES Editor
This document presents a hybrid algorithm using biogeography-based optimization (BBO) and ant colony optimization (ACO) for land cover feature extraction from remote sensing images. The algorithm first analyzes a training image to identify features that BBO and ACO classify efficiently. It then applies BBO to clusters containing these features and ACO to remaining clusters. An evaluation shows the hybrid algorithm achieves a higher kappa coefficient of 0.97 compared to 0.67 for BBO alone, indicating better classification accuracy. The authors conclude the algorithm effectively handles uncertainties in remote sensing images and future work could improve efficiency further.
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 summarizes a method for acquiring stereo image pairs with pixel-accurate ground truth correspondence information using structured light. The method involves projecting patterns of structured light onto a scene using one or more light projectors while capturing images using a pair of cameras. By decoding the projected light patterns, each pixel can be uniquely labeled, allowing trivial determination of correspondences between camera views. The structured light patterns help overcome limitations of existing stereo datasets in evaluating stereo matching algorithms.
1) Robust wavelet denoising is proposed as an improvement over traditional waveshrink and basis pursuit methods, which are less effective when noise is non-Gaussian and contains outliers.
2) The proposed method formulates robust wavelet denoising as an optimization problem that minimizes a robust loss function, such as the Huber loss function, rather than least squares.
3) Two algorithms are proposed to solve the robust wavelet denoising optimization problem: block coordinate relaxation and an interior point method. Parameter selection is also discussed.
Image Splicing Detection involving Moment-based Feature Extraction and Classi...IDES Editor
In the modern age, the digital image has taken
the place of the original analog photograph, and the forgery
of digital images has become increasingly easy, and harder
to detect. Image splicing is the process of making a
composite picture by cutting and joining two or more
photographs. An approach to efficient image splicing
detection is proposed here. The spliced image often
introduces a number of sharp transitions such as lines,
edges and corners. Phase congruency is a sensitive measure
of these sharp transitions and is hence proposed as a
feature for splicing detection. Statistical moments of
characteristic functions of wavelet sub-bands have been
examined to detect the differences between the authentic
images and spliced images. Image splicing detection can be
treated as a two-class pattern recognition problem, which
builds the model using moment features and some other
parameters extracted from the given test image. Artificial
neural network (ANN) is chosen as a classifier to train and
test the given images.
The document proposes two algorithms for fingerprint classification based on singular point detection. The first algorithm uses directional images and masks to detect core and delta point neighborhoods, then analyzes histograms to locate exact singular points. The second algorithm detects neighborhoods based on curvature and direction changes, then uses Poincare index to identify candidate points. Both aim to classify fingerprints into arch, loop, or whorl categories based on identified singular point types and positions.
We propose a flexible light field camera architecture that is at the convergence of optics, sensor electronics, and applied mathematics. Through the co-design of a sensor that comprises tailored, Angle Sensitive Pixels and advanced reconstruction algorithms, we show that—contrary to light field cameras today—our system can use the same measurements captured in a single sensor image to recover either a high-resolution 2D image, a low-resolution 4D light field using fast, linear processing, or a high-resolution light field using sparsity-constrained optimization.
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 4)Matthew O'Toole
Recent advances in both computational photography and displays have given rise to a new generation of computational devices. Computational cameras and displays provide a visual experience that goes beyond the capabilities of traditional systems by adding computational power to optics, lights, and sensors. These devices are breaking new ground in the consumer market, including lightfield cameras that redefine our understanding of pictures (Lytro), displays for visualizing 3D/4D content without special eyewear (Nintendo 3DS), motion-sensing devices that use light coded in space or time to detect motion and position (Kinect, Leap Motion), and a movement toward ubiquitous computing with wearable cameras and displays (Google Glass).
This short (1.5 hour) course serves as an introduction to the key ideas and an overview of the latest work in computational cameras, displays, and light transport.
2015-06-17 FEKO Based ISAR Analysis for 3D Object ReconstructionDr. Ali Nassib
This document discusses using inverse synthetic aperture radar (ISAR) imaging techniques to reconstruct 3D images of objects from electromagnetic scattering data. It presents the mathematical models and simulation setup used. Simulations were conducted of two thin cylinders separated by either half a wavelength or a full wavelength. When separated by half a wavelength, the cylinders were not clearly resolved due to coupling effects. But when separated by a wavelength, the two cylinders were successfully reconstructed from the simulated scattering data using inverse scattering algorithms. Future work involves reconstructing the full dyadic contrast function and performing additional experiments.
Sensor modeling and Photometry: an application to AstrophotographyLaurent Devineau
This document discusses sensor modeling and photometry techniques applied to astrophotography. It presents a case study imaging the Triangulum Galaxy using a modified DSLR camera and telescope. Key steps included estimating signals and noises from light, dark, and offset frames to characterize the sensor and extract measurements of sky background, dark current, and target object luminance. Expectations and variances of photoelectrons generated were related to measured analog-to-digital units. The techniques allowed optimizing exposure times based on read noise, guiding error, and dynamic range criteria.
[DL輪読会]Neural Radiance Flow for 4D View Synthesis and Video Processing (NeRF...Deep Learning JP
Neural Radiance Flow (NeRFlow) is a method that extends Neural Radiance Fields (NeRF) to model dynamic scenes from video data. NeRFlow simultaneously learns two fields - a radiance field to reconstruct images like NeRF, and a flow field to model how points in space move over time using optical flow. This allows it to generate novel views from a new time point. The model is trained end-to-end by minimizing losses for color reconstruction from volume rendering and optical flow reconstruction. However, the method requires training separate models for each scene and does not generalize to unknown scenes.
Neural Radiance Fields (NeRF) represents scenes as neural radiance fields that can be used for novel view synthesis. NeRF learns a continuous radiance field from a sparse set of input views using a multi-layer perceptron that maps 5D coordinates to RGB color and density values. It uses volumetric rendering to integrate these values along camera rays and optimizes the network via differentiable rendering and a reconstruction loss. NeRF produces high-fidelity novel views and has inspired extensions like handling dynamic scenes and reconstructing scenes from unstructured internet photos.
Fundamental concepts and basic techniques of digital image processing. Algorithms and recent research in image transformation, enhancement, restoration, encoding and description. Fundamentals and basic techniques of pattern recognition.
The document describes a method to measure the charge collection efficiency (CCE) profile of a CMOS active pixel sensor as a function of depth. Electron-hole pairs are generated at different depths by incident charged particles crossing pixels at a grazing angle. Tracks are analyzed to extract the most probable signal for each pixel position, generating a CCE profile. The profile is then converted from pixel position to depth by calculating the track incident angle using the total charge collected by orthogonal tracks. This method provides controlled depth-dependent charge generation to understand a sensor's response at different depths.
This document describes the concept of dual photography, which uses Helmholtz reciprocity to interchange lights and cameras in a scene. It discusses how the transposed transport matrix can be used to generate virtual captured images from virtual projected patterns. It also describes different methods used to capture the transport matrix, including fixed pattern scanning and adaptive multiplexed illumination. Limitations discussed include scenes with significant global illumination effects and situations where the camera and projector are at a large angle.
Recovering high dynamic range radiance maps from photographsPrashanth Kannan
This document summarizes a technique for recovering high dynamic range radiance maps from multiple low dynamic range photographs with varying exposures. It involves constructing an aggregate mapping from sensor irradiance to pixel values using a least squares approach to solve for the unknown camera response function and irradiance values. This allows combining exposures to reduce noise and obtain radiance maps that can be used for image-based rendering with an extended dynamic range compared to a single photograph.
This document summarizes a class on acceleration structures for ray tracing. It discusses building bounding volume hierarchies and using them to accelerate ray intersection tests. Uniform grids, kd-trees, and binary space partitioning trees are covered as approaches for spatial subdivision. The role of acceleration structures in speeding up global illumination calculations is also discussed.
This document provides an overview of digital image processing and is divided into multiple parts. Part I discusses digital image fundamentals, image transforms, image enhancement, image restoration, image compression, and image segmentation. It introduces key concepts such as digital image systems, sampling and quantization, pixel relationships, and image transforms in both the spatial and frequency domains. Image processing techniques like filtering, histogram processing, and frequency domain filtering are also summarized.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
1) The document discusses various techniques for edge detection in digital images, including differential operators, log operators, Canny operators, and binary morphology.
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This document provides an overview of image segmentation techniques. It begins with an introduction to image analysis and segmentation. It then covers various discontinuity-based techniques like point, line, and edge detection. Next it discusses edge linking and boundary detection methods. Thresholding techniques such as global, optimal, and adaptive thresholding are also covered. Finally, the document discusses region-based segmentation methods including region growing and region splitting/merging. The overall goal of the document is to introduce and explain the main categories and techniques used for image segmentation.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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Image pre-processing involves operations on images to improve image data by suppressing distortions or enhancing features. There are four categories of pre-processing methods based on pixel neighborhood size used: pixel brightness transformations, geometric transformations, local neighborhood methods, and global image restoration. Pre-processing aims to correct degradations by using prior knowledge about the degradation, image acquisition device, or objects in the image. Common pre-processing methods include brightness and geometric transformations as well as brightness interpolation when re-sampling images.
Similar to Accelarating Optical Quadrature Microscopy Using GPUs (20)
Accelarating Optical Quadrature Microscopy Using GPUs
1. Phase Unwrapping and Affine
Transformations using CUDA
Perhaad Mistry, Sherman Braganza,
David Kaeli, Miriam Leeser
ECE Department
Northeastern University
Boston, MA
4. Motivation
Phase Unwrapping used for research in In-Vitro
Fertilization (IVF) in Optical Quadrature Microscopy
Cell counts obtained after unwrapping determine viability
of embryos
Results required at close to real time to see changes in
sample
Improve cost-effectiveness of OQM and quality of
research
4
6. OQM Imaging
Pattern determined by phase
Camera 0
PBS
difference between laser beams
Camera 1
Camera 3
Mirror Phase calculated using
magnitudes captured from four
cameras
NPBS Camera 2
Mixed (M), signal only(S),
REF SIG
reference(R) and dark (D) images
Phase difference measured by
Sample
angle(E) ranges from –π to π
1 n=3 n M n − S n − Rn
E = ∑i *
4 n=0 Rn
From Mirror
Laser
angle(E) yields phase that is
required for unwrapping
Optical Quadrature Microscopy Layout
6
7. Affine Transformation
Align images to fix sample’s
position in different images Phase
Affine
Microscope’s
Unwrapping
Transforms
Frame
2x2 and 2x1 matrices Grabber
obtained from microscope
Image pixels divided among Algorithm for Affine Transform [1]
blocks of threads (x,y) = f(BlockId, ThreadID)
Each thread calculates one Load Data = Image[x][y]
pixel Includes - Rotation (θ), Scaling (s), Shearing (sh)
⎛ x' ⎞ ⎛ s(x)*cos(θ) sh(y)*sin(θ) ⎞ ⎛ x ⎞ ⎛ a ⎞
Implemented using CUDA ⎜ ⎟=⎜ ⎟⎜ ⎟+⎜ ⎟
y' ⎠ ⎝ -sh(x)*sin(θ) s(y)*cos(θ) ⎠ ⎝ y ⎠ ⎝ b ⎠
⎝
since result needed for Phase Store Image[x'][y'] = Data
Unwrapping (Uncoalesced W rites)
[1] A. K. Jain, Fundamentals of digital
image processing, Prentice Hall
7
8. Noise Removal & Phase Information
Separate “noise” only image available (Dark Image)
Dark voltage image subtracted from the mixed, signal
and reference images
Subtraction of signal image (Sn) and reference image
(Rn) due to fixed pattern levels of individual cameras
Mn = Mn − Dn and so on for Sn and Rn
1 n=3 n Mn − Sn − Rn
E = ∑i * n: camera number
4 n =0 Rn
phase = angle(E )
Square root of Rn to balance intensities for detection
8
9. Example Images for Affine Transform
Mixed Image Signal only Image
After Affine
Transform and
Noise Removal
9
Dark Image
Reference Image
10. Phase Unwrapping
Frame Phase
Affine
Grabber Unwrapping
Transforms
Optical phase difference from
interferometric image is shown
Parameter of interest is Optical
path difference which can be more
than π
Unwrapping along a line:
Sum till a gradient of π then, add
2π
In 2D if noise is present
Path dependencies while
summing
Wrapped Image
Causes accumulation errors (note range of values) 10
11. MATLAB’s Unwrap v/s Minimum LP Norm
Unwrap Using Minimum Lp
Unwrap Using MATLAB’s
unwrap() function Norm Algorithm [1]
11
[1] Dennis C. Ghiglia, Mark D. Pritt: Two-Dimensional Phase
Unwrapping: Theory, Algorithms, and Software
12. P
Minimum L Norm Algorithm
Minimize difference = (φi +1, j − φi , j )Ui , j + (φi +1, j − φi , j )Vi , j
ci , j
between gradients of −(φi , j − φi −1, j )Ui −1, j − (φi , j − φi , j −1 )Vi , j
wrapped and unwrapped
= ∆ ix, j U (i , j ) − ∆ ix−1, j U (i − 1, j ) +
ci , j
data [1]
∆ iy, jV (i , j ) − ∆ iy−1, jV (i − 1 j )
,
Nonlinear PDE since U and
where
V are data dependant
φx ,y is the unwrapped phase at (x,y)
weights
∆ x ,y and ∆ y ,y denote the wrapped phase in the
PDE solved iteratively x x
x and y direction respectively
using the Preconditioned
Conjugate Gradient Method Can be expressed as Qφ = c
[1] Dennis C. Ghiglia, Mark D. Pritt. Two-
Dimensional Phase Unwrapping: Theory, 12
Algorithms, and Software, Wiley New York
13. Preconditioned Conjugate Gradient
Solve un-weighted least ε 2 = M −2 N−2 (φ − φ − ∆x )2
∑ ∑ i +1, j i , j i , j
square phase unwrapping i =0 j =0
problem M − 2 N −2
+ ∑ ∑ (φi +1, j − φi , j − ∆iy, j )2
Minimize ε2 i =0 j =0
where φi , j is the wrapped phase at (i,j) and
Preconditioning using a
DCT needed ∆ix, j is the unwrapped phase at (i,j)
After discretizing the equation
Conjugate gradient
and taking the 2D Fourier Transform
method called after DCT
Ρ m,n
preconditioning Φ=
2cos(π m ) + 2cos(π n ) − 4
m,n
M N
where Φ and Ρ are the Fourier Transformed
versions of φ and ∆ respectively
13
14. Better DCT Implementation
Implementing N point DCT using DFT uses 2N point DFT
Another method seen in [1]
Rearrange x(n) into v(n) such that
⎡ N − 1⎤
v ( n ) = x (2 n ) 0≤n≤⎢ ⎥
⎣2⎦
⎡ N + 1⎤
= x (2 N − 2 n − 1) ⎢ 2 ⎥ ≤ n ≤ N −1
⎣ ⎦
W4kN * Real(v(n)))
DCT(x(n)) = 2*DFT(
For 2D DCT: 4x less work since N*N instead of 2N*2N
PCG is ~ 90% of LP Norm Execution time
Shuffle kernel before CUFFT call
[1] Makhoul J. A fast cosine transform
in one and two dimensions. 14
15. Minimum L Norm Algorithm
P
for k ← 0 to LP Norm Count
Calculate Data Derived Weights Preconditioning
for j ← 0 to PCG Iteration Count before CG
DCT To DFT Steps (Shuffle Kernel)
Execute CUFFT Call
Point-Wise Complex Multiplication to Get DCT Result
PCG
Scaling Step Algorithm
Execute CUFFT Call to do iDCT
Conjugate Gradient (Point Wise Matrix Operations)
end for
if Convergence exit
end for
15
16. Example Images – Phase Unwrapping
Wrapped Phase Data Unwrapped Phase Data
Images of Glass Bead and water
16
17. Example Images – Mouse Embryo
Wrapped Phase Data Unwrapped Phase Data
17
18. MATLAB External Interface (MEX)
MEX produces linked Frame Grabber
objects from C code Image
Acquisition Tool
Box
MATLAB present in our
system due to the frame
MATLAB Legacy
grabbers MATLAB Legacy
Interfaces
Interface
Gateway function in C
Yes
makes MATLAB data
(mxArray) visible to our Affine Transform Phase
Wrapper(C) Using Unwrapping
Save
linked C code MEX Wrapper (C)
Affine ?
Using MEX
No
Affine Transform Phase
& Noise Removal Unwrapping
GPU GPU code
Code(CUDA) (CUDA)
18
OQM Processing Control Flow
19. Performance (Phase Unwrapping)
Baseline GPU MEX and GPU Mex & GPU
GPU Time
Time Speedup Time(sec) Speedup
Preconditioning 11.17 1.2 9.3X 1.2 9.3X
Conjugate Grad. 2.89 0.55 5.25X 0.55 5.25X
IO Activity 0.7 0.7 1X 0.02 NA
Miscellaneous 0.79 0.51 1.53X 0.41 1.92X
7.20X
Total for Unwrap 15.55 2.97 5.24X 2.16
Baseline : Serial implementation using
FFTW for the Fourier Transform
19
21. Future Work
Study implementation of Conjugate Gradient
Study scatter operations in CUDA
Present literature shows improvements only for larger data
sizes (may be better on G200)
Multi-Gpu version for imaging scenarios where images
may be grabbed at faster rates
Presently only one image at a time acquired.
Phase Unwrapping also required for applications like
Synthetic Aperture Radar (SAR)
21
22. Conclusions
Implemented the computationally intensive Minimum Lp
Norm Phase Unwrapping and Affine Transforms on the
GPU
Not a batch-oriented process
Latency was critical, single image used at a time
Reducing latency throughout the system improves quality
of research and time to discovery in Optical Science
Laboratory
22
23. Thank You
Questions?
Perhaad Mistry
(pmistry@ece.neu.edu)