PROCEEDINGS
ICIP-94/1
/
c /\
/
Volume III of HI
November 13-16, 1994Austin Convention Center
Austin, Texas
Sponsored by
The Institute of Electrical and Electronics Engineers Signal Processing Society
IEEE Computer Society PressLos Alamitos, California
Washington Brussels • Tokyo
Contents Volume
ICIP-94 Organizing Committee HiTechnical Program Committee liii
Plenary:Radio Astronomical Imaging from Coherence Data 1
George W. Swenson, Jr.,University of Illinois at Urbana-Champaign
WAO: Magnetic Resonance Imaging
Chair:Z.-P. Liang, University of Illinois at Urbana-Champaign
Reconstructing Magnetic Resonance Spectroscopic Images Using Spatial Domain Priors 6E.M. Stokely and D.B. Twieg,University of Alabama at Birmingham
Alternative K-Space Sampling Distributions for MR Spectroscopic Imaging 11S.K. Plevritis and A. Macovski,Stanford University
Novel Sampling Schemes in Magnetic Resonance Imaging 15X. Hu, T. Parrish, and M. Patel,University of Minnesota
Optimized Data Acquisition, Reconstruction and Postprocessing Techniquesfor Quantitative Sodium Imaging 20
F.E. Boada, J.S. Gillen, and K.R. Thulborn,University of Pittsburgh Medical Center
Toward a Neuroscope: A Real-Time Imaging System for Evaluation of Brain Function 25C.S. Potter, Z.-P. Liang, CD. Gregory, H.D. Morris, andP.C. Lauterbur, University of Illinois at Urbana-Champaign
Locally Focused Magnetic Resonance Imaging 30Y. Cao and D. N. Levin,University of Chicago
Acquisition of the Karhunen-Loeve Expansion to Reduce MR Imaging Times 35J.B. Weaver and D.M. Healy, Jr.,Dartmouth-Hitchcock Medical Center
Theory, Simulation and Compensation of Physiological Motion Artifacts in Functional MRI 40D.C. Noll and W. Schneider,University of Pittsburgh
A Moving Target: Evaluating Algorithms for Removing MRI Motion Artifacts 45M. Smith, J. Zeng, and A. Crawley,University of Calgary
Magnetic Resonance Image Segmentation Using Optimized Nearest Neighbor Classifiers 49H. Yan, J. Mao, Y. Zhu, and B. Chen,University of Sidney
WA1: Motion Estimation — Model Based
Chair:T. Huang, University of Illinois at Urbana-Champaign
Estimation and Segmentation of Displacement Field using Multiple Features 53Sanghoon Sull, NASA Ames Research Center; and Narendra Ahuja,University of Illinois at Urbana-Champaign
Recursive Estimation of Camera Motion from Uncalibrated Image Sequences 58Stefano Soatto, California Institute of Technology; and Pietro Perona,Caltech and Universita di Padova
A Kalman Filter in Motion Analysis from Stereo Image Sequences ... 63J.N. Pan and Y.Q. Shi, New Jersey Institute of Technology; andC. Q. Shu, Bolt Beranek and Newman, Inc.
Stable Estimation of Image Orientation 68Leif Haglund, Linkoping University; and David J. Fleet,Queen's University
Simultaneous Motion-Disparity Estimation and Segmentation from Stereo 73Yucel Altunbasak, A. Murat Tekalp, and Gozde Bozdagi,University of Rochester
Virtual Motion: 3-D Scene Recovery using Focal Length-Induced Optic Flow 78Bijan G. Mobasseri and Sivakumar Doraiswamy, Villanova University
A Method to Interpret 3D Motion using Neural Networks 83Arata Miyauchi andAkira Watanabe, Musashi Institute of Technology; andMinami Miyauchi, Sanno College
Robust Tracking of Stochastic Deformable Models in Long Image Sequences 88Charles Kervrann and Fabrice Heitz, IRISA/INRIA
Pose Estimation of Human Face using Synthesized Model Images 93Akitoshi Tsukamoto and Chil-Woo Lee, Laboratories of Image Information,Science & Technology; and Saburo Tsuji, Osaka University
Analysis-Based Facial Expression Synthesis 98Li-an Tang and Thomas S. Huang, University of Illinois atUrbana- Champaign
WA2: Fractal Image Coding
Chair:M. Kunt, Swiss Federal Institute of Technology
On the Problem of Convergence in Fractal Coding Schemes 103Bernd Hurtgen and Stephan F. Simon,Aachen University of Technology
Fractal Coding of a Multi-View 3-D Image 107Takeshi Naemura and Hiroshi Harashima,University of Tokyo
A New Image Coding Technique Unifying Fractal and Transform Coding 112Kai Uwe Barthel, Jorg Schuttemeyer, Thomas Voye, and Peter Noll,Technische Universitat Berlin
VI
Fractal Image Coding as Generalized Predictive Coding 117David W. Lin, National Chiao Tung University
Fractal-Based Techniques for a Generalized Image Coding Method 122Mohammad Gharavi-Alkhansari and Thomas S. Huang, University of Illinoisat Urbana-Champaign
Iterative Collage Coding for Fractal Compression 127Jaroslaw Domaszewicz and Vinay A. Vaishampayan,Texas A &M University
Image Coding Based on Fractal Approximation and Vector Quantization 132I.K. Kim and R.-H. Park, Sogang University
Multi-resolution Tree Search for Iterated Transformation Theory-Based Coding 137Masayuki Kawamata, Masaki Nagahisa, and Tatsuo Higuchi,Tohoku University
Parameter Quantization in Fractal Image Coding 142Geir E. Oien, Rogaland University Center
WA3: Image Restoration II
Chair:I. Sezan, Eastman Kodak
Two Approaches for Image-Processing Based High Resolution Image Acquisition 147Y. Nakazawa, T. Saito, T. Komatsu, and T. Sekimori, Kanagawa University;K. Aizawa, University of Tokyo
Orientation-sensitive Image Processing with A/-lattice: A Novel Nonlinear Dynamical System 152Alex Sherstinsky and Rosalind W. Picard, MIT
Errorless Restoration Algorithms for Band-limited Images 157Paulo Jorge S.G. Ferreira and Armando J. Pinho,Universidade de Aveiro
A Mixture-Site Model for Edge-Preserving Image Restoration 162Jeffrey A. Fessler, University of Michigan
A Simple Algorithm for Joint Blur Identification and Image Restoration 167Yu-Li You and M. Kaveh, University of Minnesota
Computation of Bayesian Estimators for Markov Random Field Image ModelsUsing the Cluster Approximation 172
Chi-hsin Wu and Peter C. Doerschuk, Purdue University
Map and Regularized Constrained Total Least-Squares Image Restoration 177Vladimir Z. Mesarovic and Nikolas P. Galatsanos,Illinois Institute of Technology
Convex Set Theoretic Image Recovery via Chaotic Iterations of Approximate Projections 182P.L. Combettes, City College of New York
Multiscale Adaptive Image Restoration in the Wavelet Domain 187Mark R. Banham, Motorola, Inc.; andAggelos K. Katsaggelos,Northwestern University
Gradient-Projection Blind Deconvolution 192Yongyi Yang, N. P. Galatsanos, and Henry Stark,Illinois Institute of Technology
vu
WA4: Image Processing Applications
Chair:P. Silsbee, Old Dominion University
Improving the Picture Quality of Cable Television 197Pingnan Shi and Rabab K. Ward,University of British Columbia
Automatic Interpretation of Cadasters by Image Analysis Techniques 202C.C. Hsieh, H.W. Chao, B. Chen, andP.H. Shih,Institute for Information Industry
Generation of Sketch Map Drawing from Vectorized Image 207Noboru Babaguchi, Kiyoshi Tanaka, and Tadahiro Kitahashi,Osaka University
Tracking and Counting Moving People 212M. Rossi and A. Bozzoli, IRST
View Planning for Verification using Machine Vision 217Lester A. Gerhardt and Kwangik Hyun,Rensselaer Polytechnic Institute
Hand-Eye Coordination of a Robot Manipulator Based on Fuzzy Logic 221Sukir S. Kumaresan and Hua Harry Li, Texas Tech University
Storm Tracking in Doppler Radar Images 226D. Krezeski, R. E. Mercer, andJ.L. Barron,University of Western Ontario; P. Joe, King City Radar Station; andH. Zhang, University of Western Ontario
Extracting Curvilinear Features from Remotely Sensed Images usingMinimum Cost Path Techniques 231
M.R. Dobie and P.H. Lewis, University of Southampton
Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth 236M.C. Burl, Usama M. Fayyad, Pietro Perona, and Padhraic Smyth,California Institute of Technology
Image Analysis and Application Systems in Quality Evaluation andPrediction for Meat and Live Meat Animals 241
Hui L. Zhang, Doyle E. Wilson, and Gene H. Rouse,Iowa State University
WA5: Hierarchical Video Coding
Chair:J. Woods, Rensselaer Polytechnic University
A RO1 Approach for Hybrid Image Sequence Coding 245Eric Nguyen, Claude Labit, and J-M. Odobez,IRISA/INRIA
Motion-Compensated 3-D Subband Coding with MultiresolutionRepresentation of Motion Parameters 250
Jens-Rainer Ohm, Technische Universitat Berlin
via
Three Dimensional Subband Video Analysis and Synthesis with AdaptiveClustering in High Frequency Subbands 255
Jiebo Luo, Chang Wen Chen, and Kevin J. Parker, University of Rochester; andThomas S. Huang, University of Illinois at Urbana-Champaign
Hierarchical Motion Estimation with 2-Scale Tilings 260Baldine-Brunel Paul, Georgia Institute of Technology; andEric Viscito, IBM T.J. Watson Research Center
Fast and Efficient Techniques for Motion Estimation using Subband Analysis 265Shrikanth S. Narayanan, University of California, Los Angeles;Homayoun Shahri, Donald J. Youtkus, and Minsky Luo, AT&T Bell Laboratories
Motion Estimation Based on Markov Random Fields 270B. Rouchouze, P. Mathieu, T. Gaidon, and M. Barlaud,CNRS UNSA
An Efficient Algorithm for Hierarchical Compression of Video 275Mohan Vishwanath and Phil Chou,Xerox Palo Alto Research Center
Low-Bit Rate Subband Video Coding 280Christine Podilchuk, AT&T Bell Laboratories
Multi-resolution Based Algorithms for Low Bit-rate Image Coding 285Kwong H. Goh, John J. Soraghan, and Tariq S. Durrani,University of Strathclyde
WA6: Computed Imaging
Chair:M. Kaveh, University of Minnesota
Three Dimensional Reconstructions of Brains from 2-deoxyglucose Serial Section Autoradiographs 290Andreas Hess and Henning Scheich,Federal Institute for Neurobiology
Object Wavefunction Reconstruction in High Resolution Electron Microscopy 295D. Van Dyck and M. Op de Beeck, University of Antwerp; W. Coene,Philips Research Laboratories
A Method to Improve the Lateral Resolution of Ultrasonic Intravascular Imaging 299Hou Chao Huan and Jiang Hui,Chinese Academy of Sciences
Edge Detection in Ultrasound Speckle Noise 304RichardN. Czerwinski, Douglas L. Jones, and William D. O'Brien, Jr.,University of Illinois at Urbana-Champaign
Identification of Events from 3D Volumes of Seismic Data 309Peter Tu, Andrew Zisserman, Iain Mason, and Ingemar Cox,Oxford University
Phase-Error Correction for Coherent Array Imaging Systems 314Timothy J. Schulz, Michigan Technological University
On Implementation of Adaptive Local Coordinate Transformations in Optical Image Processing 319Y.B. Karasik, Carleton University
IX
WA7: Wavelet Image Coding
Chair:M. Barlaud, CNRS UNSA
Wavelet Packets-Based Image Coding using Joint Space-frequency Quantization 324Zixiang Xiong, Kannan Ramchandran, and Michael T. Orchard,University of Illinois at Urbana-Champaign; andKohtaro Asai, Mitsubishi Electric Corp.
Wavelet Packet Coding with Jointly Optimized Lattice Vector Quantization andData Rate Allocation 329
Patrice Onno and Christine Guillemot, CCETT
Nonseparable Orthogonal Linear Phase Perfect Reconstruction Filter Banks andTheir Application to Image Compression 334
Shankar Venkataraman and Bernard C. Levy,University of California, Davis
A Tree Structured Bayesian Scalar Quantizer for Wavelet Based Image Compression 339Birsen Yazici, Mary L. Comer, R. L. Kashyap, and Edward J. Delp,Purdue University
Adaptive Image Coding Based on the Discrete Wavelet Transform 343H. Jafarkhani, N. Farvardin, and C.-C. Lee,University of Maryland
Coding Gain and Spatial Localisation Properties of Discrete WaveletTransform Filter Banks for Image Coding 348
J.P. Andrew, P.O. Ogunbona, and F.J. Paoloni,University of Wollongong
Optimal Selection of Multi-dimensional Biorthogonal Wavelet Bases 353Michael G. Strintzis, University of Thessaloniki
Adaptive Wavelet Coding of Images 358James H. Kasner and Michael W. Marcellin,University of Arizona
Classified Wavelet Transform Coding of Images using Two-ChannelConjugate Vector Quantization 363
Young Huh, J.J. Hwang, and K.R. Rao,University of Texas at Arlington
Adaptive Spline-Wavelet Image Encoding and Real-Time Synthesis 368P.C. Marais, E.H. Blake, andA.A.M. Kuijk,Centrum voor Wiskunde en Informatica
Lossless Progressive Transmission of Scientific Data using Biorthogonal Wavelet Transform 373Hai Tao and Robert J. Moorhead,Mississippi State University
Digital Image Compression Based on Non-stationary and InhomogeneousMultiresolution Analyses 378
Andreas Uhl, University of Salzburg
WA8: Image Texture Modeling and Synthesis
Chair:R. Chellappa, University of Maryland at College Park
A Correlation Structure Based Approach to Neighborhood Selection inRandom Field Models of Texture Images 383
AUreza Khotanzad and Jesse W. Bennett,Southern Methodist University
An Adaptive Approach for Texture Modelling 388Michael T. Johnson and Mita D. Desai,University of Texas at San Antonio
Image Modeling using Inverse Filtering Criteria with Application to Texture Images 392Thomas E. Hall and Georgios B. Giannakis,University of Virginia
Modeling and Estimation for a Class of Multiresolution Random Fields 397Peyman Milanfar, SRI International; Robert R. Tenney,Robert B. Washburn, and Alan S. Willsky, Alphatech Inc.
Texture Analysis using Partially Ordered Markov Models 402Jennifer L. Davidson, Ashit Talukder, and Noel Cressie,Iowa State University
Transform Features for Texture Classification and Discrimination in Large Image Databases 407John R. Smith and Shih-Fu Chang,Columbia University
Multiscale Image Texture Analysis in Wavelet Spaces 412M.H. Gross, R. Koch, L. Lippert, and A. Dreger, ETH-Zurich
Multi-resolution Texture Analysis of Self-Similar Textures usingHierarchical Gaussian Markov Random Field Models 417
J. Samarabandu and R. Acharya,State University of New York at Buffalo
Demodulation of Images Modeled by Amplitude-Frequency Modulations usingMultidimensional Energy Separation 421
Petros Maragos, Georgia Institute of Technology; and Alan C. Bovik,University of Texas at Austin
Critical Markov Random Fields and Fractional Brownian Motion in Texture Synthesis 426Raja Ghozi and Bernard C. Levy,University of California, Davis
An Application of the Bivariate Pseudolikelihood to Texture Synthesis 431Carmen Olga Acuna, Bucknell University
Texture Analysis using a Generalised Wavelet Transform 436Tao-l Hsu and Roland Wilson,University of Warwick
Separability Based Tree Structured Local Basis Selection for Texture Classification 441Kamran Etemad and Rama Chellappa,University of Maryland at College Park
Texture Classification using Statistical Geometrical Features 446Yan Qiu Chen, Mark S. Nixon, and David W. Thomas,University of Southampton
XI
Likelihood-Based Texture Discrimination with Multiscale Stochastic Models 451Mark R. Luettgen, Alphatech Inc.; Alan S. Willsky, MIT;Thomas G. Allen and Robert R. Tenney, Alphatech Inc.
WA9: Image Segmentation
Chair:M. Crawford, University of Texas at Austin
Eigenstructure Approach to Region Detection and Segmentation 456Tianhu Lei and Wilfred Sewchand,University of Maryland at Baltimore
Watershed-Driven Relaxation Labeling for Image Segmentation 460Michael W. Hansen, David Sarnoff Research Center; andWilliam E. Higgins, Pennsylvania State University
A Comparison of Resolution Requirements for Boundary Estimation fromBinary and Grey Scale Images 465
Sally L. Wood, Santa Clara University
A Region-Region and Region-Edge Cooperative Approach of Image Segmentation 470R. Kara Falah and Ph. Bolon, Universite de Savoie;J.P. Cocquerez, ETIS/ENSEA
Segmentation of Object Surfaces using the Haar Wavelet at Multiple Resolutions 475James T. Miller and C. C. Li, University of Pittsburgh
Anisotropic Diffusion Pyramids for Image Segmentation 478Scott T. Acton, Oklahoma State University; Alan C. Bovik andMelbaM. Crawford, University of Texas at Austin
Image Segmentation Based on Multiresolution Filtering 483Jing Zhou, Xiang Fang, and Bijoy K. Ghosh,Washington University
Three Dimensional Segmentation of Volume Data 488Russell E. Muzzolini, Yee-Hong Yang, and Roger Pierson,University of Saskatchewan
A Knowledge-Based Approach to Volumetric Medical Image Segmentation 493Chang Wen Chen, Jiebo Luo, and Kevin J. Parker, University of Rochester;Thomas S. Huang, University of Illinois at Urbana-Champaign
Interactive Segmentation of Multi-Dimensional Medical Data withContour-Based Application of Genetic Algorithms 498
S. Cagnoni, University of Florence and MIT; A. B. Dobrzeniecki andJ.C. Yanch, MIT; R. Poli, University of Florence
3-D Range Images Segmentation Based on Deriche's Optimum Filters 503M. Djebali, M. Melkemi, and D. Vandorpe,Universite Claude Bernard
Variational Segmentation of Multi-Channel MRI Images 508Homer H. Pien, C.S. Draper Laboratory and Northeastern University; andJohn M. Gauch, University of Kansas
Integration of a Part Segmentation Based Vision System 513M. Bennamoun and B. Boashash,Queensland University of Technology
xn
Face Segmentation using Fuzzy Reasoning 518C.C. Chibelushi, F. Deravi, andJ.S. Mason, University of Wales
WPO: Medical Imaging Modalities
Chairs:J.U. Quistgaard, Advanced Technology Laboratories, Inc.T.J. Schulz, Michigan Technological University
Signal Acquisition and Processing for Magnetic Resonance Imaging 523Graham A. Wright, University of Toronto
Computational Optical Sectioning Microscopy for 3D Quantification ofCell Motion: Results and Challenges 528
James G. McNally, Washington University
Ultrasonic Image Formation: Implications for the Image Processing Practitioner 533Jens U. Quistgaard, Advanced Technology Laboratories, Inc.
*Single-Photon Emission Computed TomographyBenjamin M. W. Tsui,University of North Carolina, Chapel Hill
X-ray Crystallographic Imaging 538Peter C. Doerschuk, Purdue University
Positron Emission Tomography: Physical Models and Reconstruction Issues 543John Ollinger, Washington University
Imaging the Electrical Activity of the Heart: Direct and Inverse Approaches 548Dana H. Brooks, Northeastern University; and Robert S. MacLeod,University of Utah
WP1: Interpolation and Spatial Transformation
Chair:M. Unser, National Institutes of Health
Reconstruction of a High Resolution Image from Registration andRestoration of Low Resolution Images 553
Brian C. Tom and Aggelos K. Katsaggelos, Northwestern University; andNikolas P. Galatsanos, Illinois Institute of Technology
Affine Transformations of Images: A Least Squares Formulation 558Michael Unser, Matthew A. Neimark, and Chulhee Lee,National Institutes of Health
An Advanced Interpolation for Synthetical Animation 562Sophie-Anne Thobie, LIMSI-CNRS
A New ID FFT-Based Algorithm for Computing the MD FFT on Arbitrary Lattices 567R. Bernardini, G.M. Cortelazzo, and G.A. Mian,Universita di Padova
Performance Analysis of the TLS Algorithm for Image Reconstruction from aSequence of Undersampled Noisy and Blurred Frames 571
N.K. Bose, H.C. Kim, andB. Zhou,Pennsylvania State University
Xl l l
Registering Retinal Images using Automatically Selected Control Point Pairs 576William E. Hart and Michael H. Goldbaum,University of California, San Diego
An FIR Image Interpolation Filter Design Method Based on Properties of Human Vision 581Hong Chen and Gary E. Ford, University of California, Davis
New Overlapped Block Reconstruction for Tree-Structured Decomposition of Images 586B. Simon and B. Macq,Universite Catholique de Louvain
WP2: Video Signal Processors
Chair:T. Hsing, Bell Communications Research
A Novel Image Sensor for Video Compression 591K. Aizawa, H. Ohno, T. Hamamoto, andM. Hatori, University of Tokyo;J. Yamazaki, NHK
A 1.2 Billion Operations per Second Video Signal Processing Chip 596Rob Yates, Stephen Evans, and Peter A. Ivey,University of Sheffield
A General Purpose, Single Chip Video Signal Processing (VSP)Architecture for Image Processing, Coding and Computer Vision 601
J. Goodenough, R.J. Meacham, J.D. Morris, N.L. Seed, and P.A. Ivey,University of Sheffield
Full Custom VLSI Implementation of High-Speed 2-D DCT/IDCT Chip 606Vishnu Srinivasan and K.J. Ray Liu,University of Maryland at College Park
An Algorithm-Driven Processor Design for Video Compression 611Stephen Molloy, Brian Schoner, Avanindra Madisetti, and Rajeev Jain,University of California, Los Angeles; Roy Matic, Hughes Research Labs
Real Time Video Architecture of a Texture Generator for Digital Video Production 616H. Pavie, M. Rebiai, and F. Pinson, Thomson Broadcast; A. Smolarz,Universite de Technologie de Compiegne
Image Content Based Improvements to Locally Adaptive Video Enhancement 621Richard G. Hier and Sherman E. DeForest,DigiVision, Inc.
WP3: Architectures
Chair:J. Ghosh, University of Texas at Austin
Very High Speed Entropy Coding 625Martin Boliek, James D. Allen, Edward L. Schwartz, andMichael J. Gormish, RICOH California Research Center
Real-Time Hough/Radon Transform: Algorithm and Architectures 630Vladimir A. Shapiro and Valentin H. Ivanov,Bulgarian Academy of Sciences
xiv
Active Motion Detection and Object Tracking 635Joachim Denzler and Dietrich W.R. Paulus,Universitat Erlangen-Nurnberg
A Massively Parallel Implementation of Fractal Image Compression 640Min Xue, ESIGETEL and Universite de Paris Sud;Timothy Hanson, ESIGETEL and Gallaudet University; andAlain Merigot, Universite de Paris Sud
SIMD Parallel Calculation of Distance Transformations 645Jouko Viitanen and Jarmo Takala, VTTAutomation
Two-Dimensional Vector Median Filters on Mesh Connected Computers 650G. Angelopoulos and I. Pitas, University of Thessaloniki
PAPRICA-3: A Real-Time Morphological Image Processor 654A. Broggi and G. Conte, Universita di Parma; G. Burzio, Centro RicercheFIAT; L. Lavagno, F. Gregoretti, and C. Sansoe, Politecnico di Torino; andL.M. Reyneri, Universita di Pisa
A Highly Reconfigurable Neighborhood Image Processor Based on Functional Programming 659Neucimar J. Leite, University of Campinas; and Marcelo A. de Barros,Universidade Federal da Paraiba
Design and Implementation of a Programmable Stack Filter 664Prasad V. Lakamsani, Hong Kong University of Science and Technology;Ruikang Yang, Tampere University of Technology; Bing Zeng andMing L. Liou, Hong Kong University of Science and Technology
A Programmable Parallel Huffman Decoder 668Belle W. Y. Wei and Teresa H-Y Meng, Stanford University
Programmable Image Processing in a Memory Controller 672Ihtisham Kabir, Michael Hsieh, Walt Donovan, Aman Jabbi, andWilliam Radke, Sun Microsystems Inc.
HART, A Heterogeneous Architecture for Real-Time Prototyping,Development and Implementation of Machine Vision Applications 676
J. Goodenough, A.J. Shelley, and N.L. Seed, University of Sheffield
MJMD Image Analysis with Local Agents 681James J. Clark and Robert P. Hewes, Harvard University
WP4: Biomedical Image Processing
Chair:C. Chen, University of Rochester
Matching Deformable Atlas Models to Preprocessed Magnetic Resonance Brain Images 686Stephanie Sandor and Richard Leahy,University of Southern California
Model-Based Automatic Recognition of Blood Vessels from MR Images and its3D Visualization 691Qian Huang, IBM Almaden Research Center; and George C. Stockman,Michigan State University
A New Similarity Criterion for Retinal Image Registration 696Ana Maria Mendonca andAurelio Campilho, INEB and FEUP/DEEC;Jose Manuel Rodrigues Nunes, INEB and Hospital Geral de S. Antonio
xv
A Novel Method for Scattered Radiation Compensation in X-Ray ImagingSystems, using Partially Transparent Shields (PTS) 701
C. Fivez and P. Wambacq, Katholieke Univ. Leuven; P. Vuylsteke andE. Schoeters, AGFA-Gavaert N.V.; and A. Oosterlink, Katholieke Univ. Leuven
Morphological Classification of Cancerous Cells 706Jean-Philippe Thiran, Benoit Macq, and Jacques Mairesse,Universite Catholique de Louvain
Adaptive Multistage Nonlinear Filtering and Wavelet for Medical Image Enhancement 711Wei Qian and Laurence P. Clarke, University of South Florida
A Segmentation Technique for Cerebral NMR Images 716A. Deruyver, I.U.T. Strasbourg Sud; Y. Hode andL. Soufflet,FORENAP
Segmentation Based Linear Predictive Coding of Multispectral Images 721J. Hu and Y. Wang, Polytechnic University; P. Cahill,Cornell University Medical College
Segmentation and Features Extraction Techniques, with Applications to Biomedical Images 726Edward A. Ashton, Michel J. Berg, Kevin J. Parker, Jeffrey Weisberg,Chang Wen Chen, and Leena Ketonen, University of Rochester
Reconstruction of Dynamic 3-D Structures of Biological Objects using Stereo Microscopy 731Wen-Hung Liao, S. J. Aggarwal, and J. K. Aggarwal,University of Texas at Austin
WP5: Motion Estimation for Video Coding
Chair:B. Liu, Princeton University
Classified Variable Block Size Motion Estimation Algorithm for Image Sequence Coding 736Shih-Yu Huang, Jin-Rong Chen, Jia-Shung Wang, Kuen-Rong Hsieh, andHong-Yih Hsieh, National Tsing Hua University
An Improved Fast Feature-Based Block Motion Estimation 741Yiu-Hung Fok and Oscar C. Au,Hong Kong University of Science and Technology
Motion-Compensating Prediction within Spatiotemporal Bandpass OutputsBased on a Feature Specific Vector Representation 746
Bernhard Wegmann, Technische Universitat Munchen
A Motion Field Segmentation to Improve Moving Edges Reconstruction in Video Coding 751Iole Moccagatta, Fabrice Moscheni, Markus Schutz, and Frederic Dufaux,Swiss Federal Institute of Technology
Morphological Shape Representation of Segmented Images Based onTemporally Modeled Motion Vectors 756
P. Brigger, S. Ayer, and M. Kunt, Swiss Federal Institute of Technology
Investigating a New Visual Cue for Image Motion Estimation: "Motion-from-Smear" 761Wei-ge Chen, N. Nandhakumar, and Worthy N. Martin,University of Virginia
Cooperative Analysis of Multiple Frames by Visual Echoes 766Esfandiar Bandari and James J. Little,University of British Columbia
xvi
Discrete-Cosine/Sine-Transform Based Motion Estimation 771Ut-Va Koc and K.J. Ray Liu,University of Maryland at College Park
Low Complexity Matching Criteria for Image/Video Applications 776Mehdi Khosravi and Ronald W. Schafer,Georgia Institute of Technology
On the Motion Compensated Prediction Error using True Motion Fields 781Frank Muller, Aachen University of Technology
WP6: Software Systems
Chair:M. Hang, National Chiao Tung University
DeViouS: A Distributed Environment for Vision Tasks 786Phillip R. Romig, III and Ashok Samal, University of Nebraska, Lincoln
Automatic Generation of Image-Segmentation Processes 791Joseph M. Reinhardt and William E. Higgins,Pennsylvania State University
Automated Synthesis of Image Processing Procedures for a Large-Scale Image Database 796Steve A. Chien, Jet Propulsion Laboratory
A Software Architecture for Medical Image Processing Stations 801Giuseppe Boccignone, Universita' di Salerno; Angelo Chianese,Universita' di Napoli; Massimo De Santo, Universita' di Salerno; andA. Picariello, IRSIP-CNR
Scene Analysis System 806F. Sandakly and G. Giraudon, INRIA
Model-Based Programming for Parallel Image Processing 811Michael S. Moore, Gabor Karsai, and Janos Sztipanovits,Vanderbilt University
Image Processing Chain Construction by Interactive Goal Specification 816Olivier Capdevielle and Patrice Dalle, IRIT — Pole Image
A General Vision Problem Solving Architecture: Hierarchical Token Grouping 821Qian Huang, IBM Almaden Research Center
An Object-Oriented Optimization System 826G.S. Cunningham, KM. Hanson, G.R. Jennings, Jr., and D.R. Wolf,Los Alamos National Laboratory
Hybrid Computational Architectures for Image Segmentation 831Jason M. Daida, University of Michigan
WP7: Image Coding III
Chair:J. Biemond, Delft University
Lossy Compression of Clustered-Dot Halftones 836Rich A. Vander Kam and Robert M. Gray, Stanford University
XVH
Differential Lossless Encoding of Images using Non-linear Predictive Techniques 841Nasir D. Memon, Northern Illinois University; Sibabrata Ray andKhalid Sayood, University of Nebraska
Exaggerated Consensus in Lossless Image Compression 846Kris Popat and Rosalind W. Picard, MIT
Combining Gray Coding and JBIG for Lossless Image Compression 851Mourad Abdat and Maurice G. Bellanger, Laboratoire d'Electronique etCommunications CNAM
Adaptive Quantization without Side Information 856Antonio Ortega, University of Southern California; andMartin Vetterli, University of California, Berkeley
Progressive Image Transmission Based on Image Projections 861Rosa Lancini, CEFRIEL; and Stefano Tubaro,Politecnico di Milano
Region-Based Coding of Images using a Spline Model 866Ramin Baseri and James W. Modestino,Rensselaer Polytechnic Institute
A Novel DPCM Algorithm using a Nonlinear Operator 871Tian-Hu Yu, Chinese University of Hong Kong; andSanjit K. Mitra, University of California, Santa Barbara
Adaptive Successive Approximation Quantization of Image Waveforms withEfficient Codebook Updates 876
Christopher F. Barnes, Georgia Institute of Technology
Semi-adaptive Context-Tree Based Lossless Image Compression 881Xavier Ginesta and Seung P. Kim, Polytechnic University
Optimal Threshold Selection in Hierarchical Coders for Images and Video 884Sepideh H. Fatemi and Russell M. Mersereau, Georgia Institute ofTechnology; Kwan K. Truong, Atlanta Signal Processors, Inc.
WP8: Neural Networks
Chair:A. Zakhor, University of California, Berkeley
Probabilistic Neural Networks for Medical Image Quantification 889Tulay Adali and Yue Wang,University of Maryland at Baltimore County
Some Results on Edge Enhancement with Neural Networks 893Armando J. Pinho, Universidade de Aveiro; and Luis B. Almeida,INESC/Inst. Superior Tecnico
Self-Organizing Segmentor and Feature Extractor 898Robert D. Dony and Simon Haykin,McMaster University
Texture Classification Using Neural Networks and Discrete Wavelet Transform 903Paul Schumacher and Jun Zhang,University of Wisconsin, Milwaukee
xvni
A Neural Network for Fusing the MR Information into PET Images toImprove Spatial Resolution 908
Mikiya Sase, Naoyuki Kinoshita, and Yukio Kosugi,Tokyo Institute of Technology
Image Processing using an Image Approximation Neural Network 912Edward S. Dunstone, University of Wollongong
Motion Estimation of Partially Viewed 3-D Objects Based on a ContinuousDistance Transform Neural Network 917
Jenq-Neng Hwang and Yen-Hao Tseng,University of Washington
Classification Vector Quantization of Image Data using Competitive Learning 922Bruce E. Watkins and Murali Tummala, Naval Postgraduate School
Image Sequence Classification using a Neural Network Based ActiveContour Model and a Hidden Markov Model 926
Greg I. Chiou, Boeing Computer Services; and Jenq-Neng Hwang,University of Washington
Automatic Classification of Acoustic Sequences by Multiresolution ImageProcessing and Neural Networks 931
Steven D. Beck and Larry M. Deuser, Tracor Applied Sciences, Inc.
Human Face Recognition using Neural Networks 936M.H. Ahmad Fadzil and H. Abu Bakar,Universiti Sains Malaysia
Handwritten Chinese Character Recognition using Spatial Gabor Filters andSelf-Organizing Feature Maps 940
Da Deng, University of Hong Kong and South China University ofTechnology and Science; KP. Chan, University of Hong Kong; Yinglin Yu,South China University of Technology and Science
Size-Adaptive Neural Network for Image Compression 945Giancarlo Parodi and Filippo Passaggio, University of Genova
Applying Constructed Neural Networks to Lossless Image Compression 948Steve G. Romaniuk, National University of Singapore
Analysis-by-Synthesis and Example Based Animation with Topology Conserving Neural Nets 953Stefan Jockusch and Helge Ritter, University of Bielefeld
WP9: Color Image Processing and Representation
Chair:M. Tekalp, University of Rochester
Explosion of Multidimensional Image Histograms 958Phillip A. Mlsna and Jeffrey J. Rodriguez, University of Arizona
Adaptive Subsampling of Color Images 963Anil M. Murching and John W. Woods,Rensselaer Polytechnic University
Transmission of the Color Information using Quad-trees andSegmentation-Based Approaches for the Compression of Color Images with Limited Palette 967
Marc P. Tremblay and Andre Zaccarin, Universite Laval
xix
Color Image Compression by Moment-Preserving and Block Truncation Coding Techniques 972Chen-Kuei Yang, Ja-Chen Lin, and Wen-Hsiang Tsai,National Chiao Tung University
Color Edge Detector using Jointly Hue, Saturation and Intensity 977Thierry Carron and Patrick Lambert, Universite de Savoie
Fusing Color and Edge Information for Object Matching 982Marie-Pierre Dubuisson and Anil K. Jain,Michigan State University
Optimal Sequential Linear Interpolation Applied to Nonlinear Color Transformations 987James Z. Chang, Jan P. Allebach, and Charles A. Bouman,Purdue University
A Comparison of Techniques for the Transformation of Radiosity Values to Monitor Colors 992Peter Ferschin, Ingeborg Tastl, and Werner Purgathofer,Technische Universitat Wien
Adaptive Color Controller for Image Scanning and Printing Devices 997Gao-Wei Chang, Industrial Technology Research Institute;Yung-Chang Chen, National Tsing Hua University; andKing-Lung Huang, Industrial Technology Research Institute
Color Separation for Printing with Non-Standard Inks 1002Gabriel Marcu, Array Corporation; and Satoshi Abe, University of Tokyo
Estimation of Color Under Fluorescent Illuminants 1006H.J. Trussell and Manish S. Kulkarni,North Carolina State University
A Local Spatiocolor Analysis Applied to Pattern Segmentation 1011Alain Tremeau and Bernard Laget,Laboratoire Traitement du Signal et Instrumentation
Region Segmentation Using K-Mean Clustering and Genetic Algorithms 1016Yuukou Horita and Tadakuni Murai, Toyama University; andMakoto Miyahara, Japan Advanced Institute of Science and Technology
Color Image Segmentation by a Watershed Algorithm and Region Adjacency Graph Processing 1021Kari Saarinen, Tampere University of Technology
Segmentation of Road Scenes using Color and Fractal-Based Texture Classification 1026Alfred C. She and Thomas S. Huang,University of Illinois at Urbana-Champaign
xx