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CVGIP-GRAPHICAL MODELS AND image PROCESSING 1991年第3期53卷 240-257页

作者： GOUTSIAS, J Department of Electrical and Computer Engineering Image Analysis and Communications Laboratory The Johns Hopkins University Baltimore Maryland 21218 U.S.A.

We exploit the relationship between a general Gibbs random field and a mutually compatible Gibbs random field image, we investigate the possibility of approximating a general Gibbs random field by a mutually compatible Gibbs random field, and we study the consequences of such an approximation. This study is important, since, in some cases, various problems related to the modeling of images via Gibbs random fields may be simplified by restricting our interest to a special and convenient class of Gibbs random fields, the class of mutually compatible Gibbs random fields. A general analysis is presented, which results in some interesting conclusions about the desired relationship. We consider two approaches to the approximation problem. The first approach, which is more accurate, can be easily applied to the case of binary images. For nonbinary images this approach becomes cumbersome, since it requires the solution of a large system of nonlinear equations. The second approach, which is simpler but less accurate, is based on the direct relationship between the parameters of a general Gibbs random field and the parameters of a mutually compatible Gibbs random field. Simulation examples demonstrate various aspects of our analysis.

关键词： computer Metatheory

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Three-dimensional target recognition from fusion of dense range and intensity images 14

Three-dimensional target recognition from fusion of dense ra...

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Applications of Digital image Processing XIV 1991

作者： Ramirez, Manuel Mitra, Sunanda Computer Vision and Image Analysis Lab Texas Tech University Department of Electrical Engineering LubbockTX79409 United States

This paper describes an approach of feature extraction from range and intensity data for three-dimensional model-based target recognition systems. The range image of the object under study is acquired using a methodology based on a passive stereo-vision model. A coarse to fine strategy is used to explore the features in the images, and cepstral analyisis provides information about disparities between corresponding areas at each step. The surfaces of the 3-D target recovered from the passive stereo-vision model are represented by aspect graphs which are used in vector form as the input for a neural network classifier. © 1991 SPIE. All rights reserved.

关键词： Stereo image processing

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A novel method for computing the partition function of Markov random field images using Monte Carlo simulations

A novel method for computing the partition function of Marko...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： G. Potamianos J. Goutsias Department of Electrical and Computer Engineering Image Analysis and Communications Laboratory Johns Hopkins University Baltimore MD USA

The authors present a new Monte Carlo simulation technique for the estimation of the partition function of a general Markov random field (MRF), which results in unbiased, consistent and asymptotically efficient estimates. This technique gives extremely accurate results, as demonstrated by simulations. Use of more efficient algorithms can boost the performance and accuracy of the method, and yield more reliable estimates.< >

关键词： Markov random fields Monte Carlo methods Probability distribution Lattices image analysis Laboratories Closed-form solution Maximum likelihood estimation Equations Samarium

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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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Optical flow for tagged MR images

Optical flow for tagged MR images

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： J.L. Prince E.R. McVeigh Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Division of Magnetic Resonance Imaging Department of Radiology and Radiological Sciences Johns Hopkins Medical Institutions Baltimore MD USA

A method to reconstruct motion from sequences of tagged magnetic resonance (MR) images is presented. MR tagging is used to create a spatial pattern of varying magnetization so that objects which may otherwise have constant intensity are textured; this reduces the motion ambiguity associated with the aperture problem in computer vision. To account for the decay of the tag pattern, a new optical flow algorithm is developed and implemented. Velocity fields estimated using this algorithm are used to recursively update the implied motion reference map over time, thereby tracking the motion of individual particles. If a segmentation of the object is known at the time the tag pattern is created, then an object may be selectively tracked, using the estimated reference map to update the object's position as time progresses. Results are shown for actual MR phantom data.< >

关键词： image motion analysis image reconstruction Magnetic resonance Tagging Magnetization Apertures computer vision Motion estimation Recursive estimation Particle tracking

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image reconstruction based on human and monkey cone mosaics

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Journal of Visual Communication and image Representation 1990年第2期1卷 137-152页

作者： Costaridou, Lena Stefanou, Spyros Hirsch, Joy Orphanoudakis, Stelios Image Analysis and Computer Vision Laboratory Institute of Computer Science Foundation of Research and Technology-Hellas Heraklion Crete Greece Department of Ophthalmology and Visual Science Yale University New Haven CT United States Image Analysis and Computer Vision Laboratory Institute of Computer Science Foundation of Research and Technology-Hellas Heraklion Crete Greece Departments of Diagnostic Imaging and Electrical Engineering Yale University New Haven CT United States

The image reconstruction capacity of the actual foveal cone sampling mosaics of an adult monkey and human is investigated through computer simulations. A retinocortical mapping model in which positions are known and disorder is compensated (DC) has been implemented using classical Whittaker-Kotelnikov-Shannon (WKS) reconstruction theory and a two-dimensional hexagonal tessellation technique that maps the cone lattice onto a perfectly hexagonal grid. The DC model has been compared with a retinocortical mapping model in which cone positions are also known but position disorder is uncompensated (DU) in the reconstruction process. A control model has also been implemented using WKS reconstruction based on sampled data obtained with simulated perfectly hexagonal lattices whose Nyquist limits are equivalent to those of the human and monkey lattices. Quantitative comparisons of these models are based on the RMS error per pixel between the original and reconstructed images. Results of these simulations demonstrate a pronounced superiority of the DC over the DU model. The results of these simulations, which use "biologically correct" sampling lattices, document a potential image reconstruction advantage when foveal cone positions are known. © 1990.

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Robust morphological representation of binary images

Robust morphological representation of binary images

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： D. Schonfeld J. Goutsias Department of Electrical and Computer Engineering Image Analysis and Communications Laboratory Johns Hopkins University Baltimore MD USA

A general theory for the morphological representation of discrete and binary images is presented. Particular cases of the general scheme are shown to yield a number of useful image representations. The effect of noise degradation is studied. It is proven that, under certain assumptions, the general reduced morphological skeleton is the best morphological representation among a collection of invertible morphological image representations. This representation results in a minimal upper-bound on the average probability of error of reconstructing a binary image from its noisy representation.< >

关键词： image representation Noise robustness Degradation Skeleton image reconstruction

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Consistency and convexity in object reconstruction from projections

Consistency and convexity in object reconstruction from proj...

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IEEE International Conference on Systems engineering

作者： J.L. Prince Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

A projection-space approach for reconstruction from projections is presented. This approach uses the known convex support of the object both as a penalty term in a variational problem defined in projection-space and as a guide to the specification of optimal smoothing coefficients that may vary spatially. Partial consistency of the sinogram is provided by including mass and center-of-mass constraints in the variational formulation. An outline of the general approach and calculations for a specific example are provided. computer simulations are provided for evaluation of the performance in this special case

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An Iterative Approach To Sinogram Restoration

An Iterative Approach To Sinogram Restoration

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： J.L. Prince Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

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