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Visualizing local vector field topology

JOURNAL OF ELECTRONIC IMAGING 2000年第4期9卷 356-367页

作者： Scheuermann, G Hamann, B Joy, KI Kollmann, W Univ Calif Davis Dept Comp Sci Ctr Image Proc & Integrated Computing Davis CA 95616 USA Univ Calif Davis Dept Mech & Aeronaut Engn Davis CA 95616 USA

The visualization of vector fields has attracted much attention over the last decade due to the vast variety of applications in science and engineering. Topological methods have been used intensively for global structure extraction and analysis. Recently, there has been a growing interest in local structure analysis due to its connection to automatic feature extraction and speed. We present an algorithm that extracts local topological structure of arbitrary regions in a two-dimensional vector field. It is based on a mathematical analysis of the topological vector field structure in these regions. The algorithm deals with piecewise linear vector fields and arbitrary polygonal regions. We have tested the algorithm for well known analytic Vector fields and data sets resulting from computational fluid dynamics. (C) 2000 SPIE and IS&T. [S1017-9909(00)01104-1].

关键词： Visualization Visual analytics Computational fluid dynamics Lead Mechanics 3D image processing algorithm development Analytical research Image processing Standards development

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FLIR ATR using location uncertainty

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JOURNAL OF ELECTRONIC IMAGING 2000年第2期9卷 178-193页

作者： Liu, G Haralick, RM Univ Washington Dept Elect Engn Intelligent Syst Lab Seattle WA 98195 USA

A model-based FLIR ATR algorithm is described. It utilizes boundary contrast for target detection and recognition. Boundary contrast is related to the location uncertainty at target boundary points. A polygon model is used for deriving target centroid location uncertainty caused by the boundary point location uncertainty. The significance of the work lies in the sound mathematical models used in deriving the relationship between contrast and location uncertainty for the boundary points and the relationship between boundary point location uncertainty and centroid location uncertainty Experiment results show significantly improved performance in detection, recognition, and localization. (C) 2000 SPIE and IS&T. [S1017-9909(00)01602-0].

关键词： Detection and tracking algorithms Forward looking infrared Automatic target recognition Target detection Target recognition Signal to noise ratio Image segmentation algorithm development Error analysis Sensors

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Visualizing the process of knowledge discovery

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JOURNAL OF ELECTRONIC IMAGING 2000年第4期9卷 404-420页

作者： Han, JC Cercone, N Univ Waterloo Dept Comp Sci Waterloo ON N2L 3G1 Canada

Most existing visualization systems stress either the original data visualization or the discovered knowledge visualization, such as decision tree, neural network. rules, etc., but lack the abilities to visualize the entire process of knowledge discovery. We propose an interactive model, RuleViz, for visualizing the process of knowledge discovery and data mining. The RuleViz model consists of five components, each or which can be interacted and visualized by using different visualization techniques. According to this model two interactive systems, AViz and CViz, for visualizing the process of discovering numerical association rules and the process of learning classification rules have been implemented, respectively. To preprocess the data, each system provides users with three approaches for discretizing numerical attributes and the corresponding rule discovery algorithms. The discretization approaches and the algorithms for discovering association rules and learning classification rules are presented, and the approaches to visualizing discretized data and discovered rules are developed. The discovery of numerical association rules in AViz is based on image-based mining algorithm, while, in CViz, the classification rules are learned in terms of a logical rule induction algorithm. We also demonstrate our experimental results with AViz and CViz on the census data sets. UCI data sets, and artificial data sets. (C) 2000 SPIE and IS&T. [S107-9909(00)01304-0].

关键词： Visualization Knowledge discovery Visual process modeling Data visualization Data modeling algorithm development Mining Classification systems Systems modeling Data mining

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Mapping of two-dimensional convolution on very long instruction word media processors for real-time performance

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JOURNAL OF ELECTRONIC IMAGING 2000年第3期9卷 327-+页

作者： Managuli, R York, G Kim, D Kim, Y Univ Washington Image Comp Syst Lab Dept Elect Engn Seattle WA 98195 USA Univ Washington Image Comp Syst Lab Dept Bioengn Seattle WA 98195 USA

Programmable media processors have been emerging to meet the continuously increasing computational demand in complex digital media applications, such as HDTV and MPEG-4, at an affordable cost. These media processors provide the flexibility to implement various image computing algorithms along with high performance, unlike the hardwired approach that has provided high performance for a particular algorithm, but lacks flexibility. However, to achieve high performance on these media processors, a careful and sometimes innovative design of algorithms is essential. In addition, programming techniques, e.g., software pipelining and loop unrolling, are needed to speed up the computations while the data flow can be optimized using a programmable DMA controller. In this paper, we describe an algorithm for two-dimensional convolution, which can be implemented efficiently on many media processors. Implemented on a new media processor called the MAP1000, it takes 7.9 ms to convolve a 512x512 image with a 7x7 kernel, which is much faster than the previously reported software-based convolution and is comparable with the hardwired implementations. High performance in two-dimensional convolution and other algorithms on the MAP1000 clearly demonstrates the feasibility of software-based solutions in demanding imaging and video applications. (C) 2000 SPIE and IS&T. [S1017-9909(00)00203-8].

关键词： Convolution Image processing algorithm development Imaging systems Signal processing Digital signal processing Data processing Computer programming Multimedia Video

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Automatic recovery of invisible image watermarks from geometrically distorted images

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JOURNAL OF ELECTRONIC IMAGING 2000年第4期9卷 477-483页

作者： Braudaway, GW Mintzer, F IBM Corp Thomas J Watson Res Ctr Yorktown Heights NY 10598 USA

One method of attacking an imbedded invisible watermark is to create a derivative image that is geometrically distorted relative to the original. One attack, developed at Cambridge University, is called "StirMark."(1) image-distorting methods modify images so subtly that the changes are essentially unnoticeable to a viewer. However, their effect on invisible watermarks can be devastating, rendering them unextractable. In this paper, an automated countermeasure to image-distorting attacks will be described. Employing an unmarked copy of the original image as a reference, the possible distortion in a suspect image is first detected by the method, then measured, and finally reversed, producing a restored image approximately geometrically aligned with the original. Using a robust invisible watermarking method described previously by one of the authors to produce a watermarked image, "StirMark" to distort the watermarked image, and a copy of the original unmarked Image for reference, the restoration method is demonstrated to be sufficient by showing successful extraction of the imbedded watermark from a restored image. (C) 2000 SPIE and IS&T. [S1017-9909(00)00904-1].

关键词： Digital watermarking Image restoration Distortion Image compression Image processing Image visualization Composites algorithm development Digital imaging Matrices

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Performance comparison of convex-nonquadratic priors for Bayesian tomographic reconstruction

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JOURNAL OF ELECTRONIC IMAGING 2000年第3期9卷 242-250页

作者： Lee, SJ Paichai Univ Dept Elect Engn Seo Ku Taejon 302735 South Korea

Bayesian methods have formed the core of the development of reconstruction algorithms for emission tomography. In particular, there has been considerable interest in edge-preserving prior models, which are associated with smoothing penalty functions that are nonquadratic functions of nearby pixel differences. In spite of several advantages of nonconvex prior models, their use in routine applications has been hindered by several factors, such as the computational expense due to the nonconvexity of penalty functions and the difficulty in the selection of hyperparameters. We note here that, by choosing a penalty function which is nonquadratic but is still convex, both the problem of nonconvexity involved in some nonquadratic priors and the edge-oversmoothing problem of conventional quadratic priors may be avoided. In this paper, we use a class of two-dimensional smoothing splines with low (first) and high (second) spatial derivatives applied to convex-nonquadratic (CNQ) penalty functions. To compare quantitative performance of our new priors, we use the quantitation of bias/variance and total squared error over noise trials. Our numerical results show that a linear combination of first- and second-order spatial derivatives applied to CNQ penalty functions improves reconstructions in terms of total squared error. (C) 2000 SPIE and IS&T. [S1017-9909(00)00202-6].

关键词： Data modeling Reconstruction algorithms Positron emission tomography Tomography algorithm development Performance modeling Image processing Monte Carlo methods Statistical modeling Optimization (mathematics)

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Entropy-constrained learning vector quantization algorithms and their application in image compression

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JOURNAL OF ELECTRONIC IMAGING 2000年第4期9卷 495-508页

作者： Karayiannis, NB Zervos, N Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA Lucent Technol Bell Labs Holmdel NJ 07733 USA

This paper presents entropy-constrained learning vector quantization (ECLVQ) algorithms and their application in image compression. The development of these algorithms relies on reformulation, which is a powerful new methodology that essentially establishes a link between learning Vector quantization and clustering algorithms developed using alternating optimization. ECLVQ algorithms are developed in this paper by reformulating entropy-constrained fuzzy clustering (ECFC) algorithms, which were developed by minimizing an objective function incorporating the partition entropy and the average distortion between the feature vectors and their prototypes. The proposed algorithms allow the gradual transition from a maximally fuzzy partition to a nearly crisp partition of the feature vectors during the learning process. This paper presents two alternative implementations of the proposed algorithms, which differ in terms of the strategy employed for updating the prototypes during learning. The proposed algorithms are tested and evaluated on the design of codebooks used for image data compression. (C) 2000 SPIE and IS&T. [S1017-9909(00)00304-4].

关键词： Prototyping algorithm development Quantization Distortion Fuzzy logic Image compression Annealing Reconstruction algorithms Optimization (mathematics) Image quality

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On the design of neuro-fuzzy hybrid multichannel filters to remove impulsive noise for color image restoration

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JOURNAL OF ELECTRONIC IMAGING 2000年第2期9卷 117-139页

作者： Tsai, HH Chen, SH Yu, PT Natl Chung Cheng Univ Dept Comp Sci & Informat Engn Chiayi 62107 Taiwan

This paper proposes a novel class of multichannel filters called neuro-fuzzy hybrid multichannel (NFHM) filters to simultaneously achieve three objectives: noise attenuation, chromaticity retention, and edges or details preservation. NFHM filters are characterized by a set or fuzzy rules (structure knowledge) such that they are capable of effectively fusing together the useful filtering merits from vector median, vector directional, and identity filters to further. improve the filtering performance of the conventional filters. Moreover, we adequately exploit the functional equivalence between fuzzy inference systems and radial-basis function networks on the optimal design of NFHM filters such that NFHM filters can be optimized by neuro-learning techniques based on the radial-basis function networks to obtain adaptive fuzzy rules for the different window contents. Finally, extensive simulation results demonstrate that the filtering performance of NFHM filters is superior to that of other proposed filters. (C) 2000 SPIE and IS&T. [S1017-9909(00)02102-4].

关键词： Image filtering Digital filtering Fuzzy logic Nonlinear filtering Neurons Visualization Fuzzy systems Optical filters Signal attenuation algorithm development

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Qualitative analysis of two reconstruction techniques and their application in dentistry

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JOURNAL OF ELECTRONIC IMAGING 2000年第4期9卷 385-393页

作者： Nonato, LG Minghim, R Shimabukuro, MH Univ Sao Paulo Inst Ciencias Matemat & Comp BR-13560970 Sao Carlos SP Brazil UNESP Pres Prudente SP Brazil

Although visualization in the field of dentistry has some of the same requirements as the medicine field, the differences in goal demand specific approaches. This paper reports on the implementation of two fundamentally different approaches to reconstruction of structures from planar cross sections and their application to dentistry data. One of the approaches was an implementation of a distance-based sampling technique, and the other is a new algorithm, based on the Delaunay triangulation. Both were tested using contour data of teeth and the results are compared here in the light of the target applications, which are teaching and training dentistry, as well as simulation of dental procedures and illnesses, Widely mentioned problems encountered in local reconstruction methods such as marching cubes for these cases ate clearly illustrated in this paper, and a very satisfactory alternative is given. (C) 2000 SPIE and IS&T. [S1017-9909(00)01504-X].

关键词： Reconstruction algorithms Dentistry Teeth Visualization 3D modeling Data modeling Visual process modeling algorithm development Computer simulations Medicine

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Fast algorithms for histogram matching: Application to texture synthesis

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JOURNAL OF ELECTRONIC IMAGING 2000年第1期9卷 39-45页

作者： Rolland, JP Vo, V Bloss, B Abbey, CK Univ Cent Florida Sch Opt Orlando FL 32816 USA Univ Cent Florida CREOL Sch Elect Engn & Comp Sci Orlando FL 32816 USA Univ Cent Florida Sch Elect Engn & Comp Sci Orlando FL 32816 USA Univ Arizona Program Appl Math Tucson AZ 85724 USA

Texture synthesis is the ability to create ensembles of images of similar structures from sample textures that have been photographed. The method we employ for texture synthesis is based on histogram matching of images at multiple scales and orientations. This paper reports two fast and in one case simple algorithms for histogram matching We show that the sort-matching and the optimal cumulative distribution function (CDF)-matching (OCM) algorithms provide high computational speed compared to that provided by the conventional approach. The sort-matching algorithm also provides exact histogram matching. Results of texture synthesis using either method show no subjective perceptual differences. The sort-matching algorithm is attractive because of its simplicity and speed, however as the size of the image increases, the OCM algorithm may be preferred for optimal computational speed. (C) 2000 SPIE and IS&T. [S1017-9909(00)00601-2].

关键词： Mammography algorithm development Image processing Image quality Medical imaging Computer graphics Computer science Electrical engineering Photography Volume rendering

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