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Asilomar Conference on Signals, Systems & computers

作者： G.W. Cook E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The problem inherent to any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is to implement the algorithms on a parallel supercomputer. The authors address the parallel implementation of the JPEG still image compression standard on the MasPar MP-1, a massively parallel SIMD computer. They demonstrate that the greatest difficulty lies not with the compression algorithm per se, but with the speed bottleneck that arises in the output of the compressed image. They develop a parallel output algorithm which addresses this problem and present results which show real-time performance on 1024/spl times/1024 images.< >

关键词： High performance computing Transform coding image coding image storage Digital images Video compression Bandwidth Supercomputers Concurrent computing Compression algorithms

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Local estimation of Gaussian-based edge enhancement filters using Fourier analysis

Local estimation of Gaussian-based edge enhancement filters ...

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1993 IEEE International Conference on Acoustics, Speech, and Signal processing

作者： B. Wang D.M. Rose A.A. Farag E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma . An estimation procedure for sigma using Fourier analysis is described. The measure is easy to implement and is based totally on the image at hand. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support, which is needed to enhance the edges. Other equivalent bandwidth definitions can be used to obtain a measure of the frequency spread in the smoothed image (e.g., the mean-square bandwidth).< >

关键词： Gaussian processes Low pass filters Shape Filtering Frequency Mathematics computer science computer vision image processing image segmentation

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A STUDY OF THE GENERALIZED MORPHOLOGICAL FILTER

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CIRCUITS SYSTEMS AND SIGNAL processing 1992年第1期11卷 229-252页

作者： SONG, JS DELP, EJ 1. Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University 47907 West Lafayette Indiana USA

A new class of morphological filters is proposed for image enhancement. The filter, known as the generalized morphological filter (GMF), uses multiple structuring elements and combines linear and morphological operations. The GMF can be designed to suppress various types of noise yet preserve geometrical structure in an image. A study of several aspects of the performance of the filter is presented. The study includes geometrical feature preservation, noise suppression, structuring element selection, and the root signal structure. For the sake of comparison, averaging and median filters are also used in the experiments and corresponding figures of merit of the performance of the filter. The empirical study shows that the generalized morphological filter possesses effective noise suppression with reduced geometrical feature blurring.

关键词： Signal Filtering And Prediction

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On empirical estimation of the parameters of edge enhancement filters

On empirical estimation of the parameters of edge enhancemen...

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IEEE International Conference on Systems, Man, and Cybernetics, SMC 1992

作者： Farag, Aly A. Cao, Yu Rose, D.M. Delp, Edward J. Engineering Mathematics and Computer Science Dept. Speed Scientific School University of Louisville LouisvilleKY40292 United States Computer Vision and Image Processing Lab. School of Electrical Engineering Purdue University West LafayetteIN47907 United States

ISBN: (纸本)0780307208

Edge-based image segmentation is a two-stage process;edge enhancement followed by edge linking. Modern approaches for edge enhancement use either the gradient of the Gaussian operator (VG) or the Laplacian of the Gaussian operator (∇2G). Both operators maximize the energy of the output and both can be performed as the cascade of two operations: a filtering operation with a Gaussian filter followed by a differentiation operation (∇ or ∇2). The filtering operation provides the smoothing or the regularization needed to transform numerical differentiation from an ill-posed problem to a well-posed one. The Gaussian filter is specified by one parameter only, the standard deviation σ. The filter's spatial support is a function of σ. In this paper, an empirical measure is described for the selection of the Gaussian filter's spatial support using the power spectrum density of the input image. © 1992 IEEE.

关键词： image segmentation

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Real-time pattern recognition by joint-Fourier transform correlation

Real-time pattern recognition by joint-Fourier transform cor...

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International Conference on Manufacturing Automation 1992

作者： Poon, Ting-Chung Pieper, Ronald J. Optical Image Processing Laboratory Bradley Department of Electrical Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Department of Electrical and Computer Engineering Naval Postgraduate School MontereyCA93943 United States

Two commonly used optical correlation techniques, matched spatial filtering and joint-Fourier transform correlation, are briefly reviewed. A recently proposed real-time joint-Fourier transform correlation is then disc... 详细信息

关键词： Fourier transforms

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On empirical estimation of the parameters of edge enhancement filters

On empirical estimation of the parameters of edge enhancemen...

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IEEE International Conference on Systems, Man and Cybernetics

作者： A.A. Farag Y. Cao D.M. Rose E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The authors develop an empirical measure for the selection of the Gaussian filter that is commonly used for edge enhancement. The measure is based totally on the image at hand. Edge enhancement by a Gaussian filter has two distinct advantages: (1) the filter is fully described by a single parameter, the standard deviation sigma ; (2) the two-dimensional filter is separable and can be easily implemented. The filter's spatial support is a function of sigma . This support is normally in the range of +or-3.5 sigma . An empirical measure is described for the selection of the Gaussian filter's spatial support using the power spectrum density of the input image. Classic Fourier analysis is used to obtain a measure for the spatial support of the Gaussian filter given a particular image. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support needed to enhance the edges.< >

关键词： Parameter estimation Low pass filters image edge detection image segmentation Joining processes Smoothing methods Frequency estimation Density functional theory Shape Mathematics

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Automatic neural arbor reconstruction

Automatic neural arbor reconstruction

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： P.M. Gregson Computer Vision and Image Processing Laboratory Department of Electrical Engineering Technical University of Nova Scotia Halifax NS Canada

An algorithm for detecting neural processes in serial optical sections for use in an automated three-dimensional neural reconstruction system is presented. This parsimonious, nonlinear, psychophysically motivated algorithm addresses the problems specific to neural element detection and localization, viz., images with minimal resolution, operators with small spatial supports, highly curved, filamentous features, large variation in feature intensity profile, poor signal-to-noise ratio, and determination of depth without stereo. One first finds the magnitude and orientation of the maximum intensity second directional derivative. A family of curves is locally fitted to these data, and the projections of the data on the curve family are found. If a pixel lies on a curve with sufficient total projection, it is labeled with the magnitude, orientation, curvature, spatial extent, and element displacement. Depth is interpolated from the spatial extent data for corresponding neighborhoods in three adjacent (in depth) images by using an approximation to the depth-dependent optical point spread function. Experimental results using photomicrographs of cat visual cortex are presented.< >

关键词： image reconstruction computer vision Displays Spatial resolution Neural networks Nonlinear optics Optical interconnections Neurons image processing Laboratories

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A path metric for sequential search and its application in edge linking

A path metric for sequential search and its application in e...

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IEEE International Conference on Systems, Man and Cybernetics

作者： A.A. Farag E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The authors develop a path metric for sequential search based on the linear model. The metric forms the heart of an edge-linking algorithm that combines edge elements enhanced by an optimal filter. From a starting node, transitions are made to the goal nodes by a maximum likelihood metric. This metric requires only local calculations on the search space and its use in edge linking provides more accurate results than other linking techniques.< >

关键词： Joining processes image edge detection Filters Application software Heart Layout Decoding Mathematics computer science computer vision

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INVARIANT RECOVERY OF CURVES IN M-DIMENSIONAL SPACE FROM SPARSE DATA

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND vision 1990年第3期7卷 480-490页

作者： STEVENSON, RL DELP, EJ Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette Indiana 47907 USA

We address the problem of reconstructing a smooth curve from sparse and noisy information that is invariant to the choice of the coordinate system. Tikhonov regularization is used to form a well-posed mathematical problem statement, and conditions for an invariant reconstruction are given. The resulting functional minimization problem is shown to be nonconvex. Approximations to the invariant functional are often used to form a convex problem that can be solved efficiently. Two common approximations, those of cubic and weighted cubic splines, are detailed, and examples are given to show that the approximations are often invalid. To form a valid approximation to the invariant functional we propose a two-step algorithm. The first step forms a piecewise-linear curve, which is invariant to the coordinate system. This piecewise-linear curve is then used to construct a parameterization of the curve for which we can make a valid approximation to the invariant functional. Examples are given to demonstrate the effectiveness of the algorithm, and two example applications for which the invariant property is important are given.

关键词： Algorithms Curvature Inverse problems Machine vision Reconstruction algorithms Strain

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A TECHNIQUE FOR THE VISUALIZATION AND ANALYSIS OF CARDIAC WALL MOTION BY TWO-DIMENSIONAL ECHOCARDIOGRAPHY

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IEEE TRANSACTIONS ON MEDICAL IMAGING 1989年第1期8卷 104-106页

作者： MELENDO, EG DELP, EJ Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

A technique is presented that can be used in the visualization and analysis of cardiac wall motion abnormalities by digital two-dimensional echocardiography. This technique is based on the use of a curvature function extracted from the endocardial boundary locations and can be used for shape or shape change analysis of the heart. The authors call the locations of high absolute curvature landmarks. Identification of landmarks on the endocardial boundary provides a simplified but powerful description of the boundary that allows visualization and analysis of wall motion. The simplification of the heart beating process is an excellent tool for the identification of infarcted areas of the heart.

关键词： Visualization Endocardium curvature function Cardiac wall motion 2D Echocardiography landmarks

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