Lateral Interaction in Accumulative Computation: Motion-Based Grouping Method

An investigation into acoustooptic (AO) correlation and spectrum analysis using partially coherent light is presented. The salient feature of the processing architectures is the implementation of a white-light source to reduce coherent artifact noise at the detector plane. In all information processing operations the Bragg cell is amplitude modulated to perform linear processing of light in complex amplitude. Pure sinusoidal signals with no input noise were used to drive the AO cells to isolate the effects of the multiplicative phase noise. This phase noise arises from random thickness variations and refractive-index fluctuations. Two signal-to-noise ratio (SNR) measurements are used to compare partially coherent light and laser light for the same signal processing architectures. A theoretical treatment is given to quantify the effects of the spatial and temporal coherence on these SNR measurements. Finally, the effects of the temporal and spatial coherence on the correlation peak intensity for a space-integrating and a time-integrating architecture is described. Similarly these effects are studied in the spectral estimation peak for the spectrum analyzer.

The goal of this book was to introduce the reader to the recent advances in the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). Our original motivation was the observation that more and more often, measured data in the form of images are being used as part of the simulation pipeline, and that error propagation and uncertainty quantification—starting from images but then moving through the pipeline—are important to understanding the ending result of this scientific or engineering process. To analyze the image processing pipeline, we have presented concepts that enable error propagation to be formulated with a set of basic operations: the idea of stochastic images and corresponding (numerical PDE) operations on those images. From this perspective, one approach commonly used within the engineering literature is to employ Monte Carlo sampling techniques to attempt to quantify the impact of errors and variability on an engineering pipeline. Within the uncertainty quantification world, alternative approaches such as the class of generalized polynomial chaos (gPC) methods, which make assumptions about the ability to approximate the process of interest through polynomial approximations, have gained traction as a way of accelerating the convergence of the error and uncertainty quantification process in a computationally tractable way. In this book, we have shown the results of our exploration of the use of the gPC methodology for image processing and computer vision problems. We have relied on the fact that all the prerequisites of the gPC framework (e.g., finite variance, smoothness in the stochastic space, etc.) are intrinsically satisfied in the image processing context. In particular, we have shown how the generalized polynomial chaos (gPC) approach and its corresponding rules for computation (e.g., sums, products, projections on the gPC space, etc.) lead to straightforward generalizations to image processing and computer vision techniques. We have shown that the gPC methodology, when combined with image processing and computer vision techniques, provides a powerful approach to error propagation and uncertainty quantification, and to accessing system sensitivity.

The subject’s task in conventional perimetry is to detect an incremental spot of light on a uniform background. Recent evidence indicates that, at least in glaucoma, this task can be insensitive to large amounts of neural damage. In an attempt to find more effective ways to detect early glaucomatous damage, we are developing alternative perimetric techniques that are based on pattern discrimination rather than light detection. The subject fixates a small square at the center of a large field of dynamic random dots and tries to detect a patch of non-random, or coherent, dots embedded in the background. The stimuli are displayed on a projection CRT, and all test target parameters, including position, size, shape, exposure duration, dot density, dot arrangement and dot dynamics, are under computer control. In particular, spatial and temporal coherence parameters are defined in terms of the spacing and motion of the target dots.We have obtained preliminary control data and glaucoma patient data for four different static protocols that test different stimulus parameters: size and exposure duration thresholds for fully coherent targets, and spatial coherence and temporal coherence thresholds for large, long-duration targets. Our results suggest that the temporal coherence test may be especially sensitive to early glaucomatous defects.KeywordsRetinal Nerve Fiber LayerBlind SpotSpatial CoherenceTemporal CoherencePattern DiscriminationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Partially coherent illumination provides significant advantages such as speckle-free imaging and enhanced optical sectioning in optical microscopy. The knowledge of the spatial and temporal coherence is crucial to obtain accurate quantitative phase imaging (QPI) of specimens such as live cells, micrometer-sized particles, etc. In this Letter, we propose a novel technique for illumination coherence engineering. It is based on a DMD projector providing fast switchable both multi-wavelength and spatial coherence design. Its performance is experimentally demonstrated for QPI with different spatial coherence states.

The growing demand for sustainable and energy-efficient buildings has highlighted the need for reliable and accurate methods to detect fenestration deterioration and assess UV radiation transmission. Traditional detection techniques, such as spectrophotometers and radiometers, discussed in Part I, are often expensive and invasive, necessitating more accessible and cost-effective solutions. This study, which is Part II, provides an in-depth exploration of the concepts and methodologies underlying UV bandpass-filtered imaging, advanced image processing techniques, and the mechanisms of pixel transformation equations. The aim is to lay the groundwork for a unified approach to detecting ultraviolet (UV) radiation transmission in fenestration glazing. By exploiting the capabilities of digital imaging devices, including widely accessible smartphones, and integrating them with robust segmentation techniques and mathematical transformations, this research paves the way for an innovative and potentially democratized approach to UV detection in fenestration glazing. However, further research is required to optimize and tailor the detection methods and approaches using digital imaging, UV photography, image processing, and computer vision for specific applications in the fenestration industry and detecting UV transmission. The complex interplay of various physical phenomena related to UV radiation, digital imaging, and the unique characteristics of fenestration glazing necessitates the development of a cohesive framework that synergizes these techniques while addressing these intricacies. While extensively reviewing existing techniques, this paper highlights these challenges and sets the direction for future research in the UV imaging domain.

Interruption/Interaction/Collaboration: A Critical Appraisal of the Textual @traction Interactive Event

First Page

Color image segmentation is an important technique in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, it is still a complex task especially when there are noises in the images, which have not been studied in much detail.

Object tracking is a major technique in image processing and computer vision. In this paper, we propose a new robust feature-based tracking scheme by employing adaptive classifiers to match the detected keypoints in consecutive frames. The novelty of this paper is that the design of online boosting is combined with the invariance of local features so that the classifier-based descriptions are formed in association with the scale and rotation information. Furthermore, we introduce a sample weighting mechanism in the on-line classifier updating, for the subsequent tracking. Experimental results demonstrate the robustness and accuracy of our proposed technique.

This paper presents a prediction based spatio-temporal seam carving scheme for video retargeting. It resizes the video maintaining appropriate balance between spatial and temporal coherence. In a video frame, the proposed approach finds a ‘temporal’ seam by using Kalman filter estimation and then modifies it with the help of ‘spatial’ seam considering both spatial and temporal coherency. Unlike image retargeting, it is of utmost importance in retargeting a video frame to consider temporal coherency along with spatial coherency to remove or replicate unimportant background portion. This will ensure that insignificant amount of motion artifacts are introduced during resizing. The proposed Kalman filter based approach not only predicts a spatio-temporal seam to mark a portion of the frame where there is more possibility of having spatially and temporally coherent seam, but also has low time complexity. The proposed approach outperforms other state-of-the-art video retargeting methods which is illustrated by experimental results.

Study on influence of concave geometry shoulder tool in Friction Stir Welding (FSW) by using Image Processing and Acoustic Emission Techniques

Coherent light sources have been demonstrated based on a wide range of nanostructures, however, little effort has been devoted to probing their underlying coherence properties. Here, we report long-range spatial coherence of lattice plasmon lasers constructed from a periodic array of gold nanoparticles and a liquid gain medium at room temperature. By combining spatial and temporal interferometry, we demonstrate millimeter-scale (∼1 mm) spatial coherence and picosecond (∼2 ps) temporal coherence. The long-range spatial coherence occurs even without the presence of strong coupling with the lattice plasmon mode extending over macroscopic distances in the lasing regime. This plasmonic lasing system thus provides a platform for understanding the emergence of long-range coherence from collections of nanoscale resonators and points toward novel types of distributed lasing sources.

Computer vision is a multidisciplinary field that cannot be separated with image processing techniques and Neuro-Computing specifically Deep Learning (DL) algorithms, in recent time DL techniques enable computer vision to understand the content of an image, moreover, it is working hand in hand with image processing techniques because image preprocessing are essential components in digital image analysis. Therefore, the remarkable advancement recorded by computer vision today such as in remote sensing, security, medical imaging and robotics etc. The aim of this research work was to explored the technical and theoretical contributions of image processing techniques and DL algorithms to computer vision. A systematic method of literature review was adapted. Basic image processing techniques such as standardization, denoising, filtering, and segmentation are clearly explored, concept of DL algorithms are briefly discussed, recent reviewed articles (from 2018 to date) are obtained from top journals in computer vision thus; IEEE, Elsevier and ISPR and tabulated as a major source of information for this work. We have shown some of the software’s used for the implementation of deep learning researches in computer vision. Finally we concludes and give recommendations based on our findings.

: For many years, the 6.1 basic research communities have focused on the effects of internal waves on temporal coherence; whereas, Navy applied programs are more concerned with the randomizing effect of the combination of bottom bathymetry variations and platform motion on array (spatial) coherence. We find that it is not possible to isolate these two causes in the shallow ocean. In the deep ocean and for propagation by refracted paths, one need only consider the effects of internal waves to understand coherence. But in shallow oceans, propagation is generally by reflected paths and bottom variability can and does affect coherence and often is more randomizing that internal waves. We have found that for very low frequencies the bottom bathymetry variation are a small fraction of the acoustic wavelength and the bottom appears flat and internal waves alone determine coherence. At very high frequencies the bottom variations are a large fraction of the wavelength and so even the slightest sound speed variations randomize and de-correlate the signal even without internal waves. But for the practical mid-frequency range, (400Hz to 3kHz), the effects of each cause are interwoven and generally inseparable. For many years, the 6.1 basic research communities have focused on the effects of internal waves on temporal coherence; whereas, Navy applied programs are more concerned with the randomizing effect of the combination of bottom bathymetry variations and platform motion on array (spatial) coherence. We find that it is not possible to isolate these two causes in the shallow ocean. In the deep ocean and for propagation by refracted paths, one need only consider the effects of internal waves to understand coherence. But in shallow oceans, propagation is generally by reflected paths and bottom variability can and does affect coherence and often is more randomizing that internal waves.

Narrow directional steerable filters in motion estimation