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IEEE SIGNAL PROCESSING SOCIETY /| /|
/ |ICIP / |
1995 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING /__|____/ |
October 23-26, 1995 | |____|__|
Hyatt Regency Crystal City | / | /
Washington, D.C., USA | / 95 | /
|/______|/
ON-LINE INFORMATION
NEW Information: Session Titles, Tutorials, Registration, Hotels
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WWW address
ftp site: ftp.ee.princeton.edu/pub/ICIP95
information: icip95@ieee.org See instructions at end of message.
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Tel: 409-696-6596
Fax: 409-696-6653
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ICIP-95 PLENARY SESSIONS
Coding with Embedded Functionality - MPEG4 Content-Based Coding
Dr. Cliff Reader
Recent Developments in Medical Imaging and Image Processing
Prof. Gabor Herman
Image Processing and Analysis: What, Why, and How
Prof. Azriel Rosenfeld
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SPECIAL SESSIONS
Video on ATM Networks
Digital Libraries
Tele-Medicine
Color and Printing
Non-linear Dynamics in Image Processing
Image Processing in Manufacturing and Materials Research
Document Image Processing
Signal and Image Processing Education
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TECHNICAL SESSIONS
Monday, October 23, 1995
Morning Afternoon
Multiresolution Non-Linear and Multi-Resolution Filters
Architectures and Software Structure and Motion Estimation
Vector Quantization I Applications I
Real and Synthetic Aperture Radar Restoration/Enhancement
Image Enhancement Morphology
Motion Estimation I Motion-Based Video Coding
Image Analysis Wavelet Compression
Image Coding I Computed Imaging
Tuesday, October 24, 1995
Image Restoration I Stereo and Shape
Image Coding II Low Bit Rate Video Coding
Parallel Algorithms Tomographic Theory and Algorithms
Multi-Dimensional Filtering Medical Applications I
Edge Detection Image Restoration II
Motion Estimation II Video Compression I
Multimedia Applications Facial Image Processing
Image Models Object Recognition
Wednesday, October 25, 1995
Image Segmentation Object Recognition
Vector Quantization II Wireless and Video Rate Control
Image Rendering and System Design Document Image Processing
Hardware Implementation
Medical Applications II Motion Segmentation and Estimation
Video Compression II Applications II
Fusion and Registration Image Segmentation Applications
Fractal Coding Image Coding III
Image Analysis II
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TUTORIAL DAY - Thursday, October 26, 1995
SESSION SA1:
Markov Random Fields and Stochastic Image Models
Time: 9:00 am - 12:00 noon
Lecturer: Charles A. Bouman
Purdue University
In recent years, Markov random field (MRF) image models have been
successfully applied in a wide variety of Bayesian image processing
applications. The two primary advantages of MRF's are simple structure and
accurate modeling of non-Gaussian image characteristics such as edges. This
tutorial will review the history, current research and future directions of
MRF's and other related stochastic image models in image processing
applications. Specific topics will include causal AR models, simultaneous
AR models, Ising and other discrete MRF models, critical temperature
behavior, continuous MRF models, MRF parameter estimation, simulation and
annealing, regularization and MAP estimation, and multiscale stochastic
models.
SESSION SA2:
Splines, Atomic Spaces, and Wavelets
Time: 9:00 am - 12:00 noon
Lecturer: Akram Aldroubi
National Institutes of Health
Polynomial spline functions and atomic representations in general result in
a characterization of continuous functions by discrete signals that is well
adapted for digital processing. These representations provide a
generalization of Shannon's sampling theory that is useful for implementing
continuous operators using fast digital filtering algorithms. In
particular, we will show how to design efficient algorithms for image
interpolation, edge detection, noise reduction, and geometric image
spline spaces is also well adapted for constructing fast multi-scale
processing algorithms that start their computations at low resolution and
refine the solution as they switch to finer scales. This is related to
multigrid processing and is useful in solving problems with high
computational cost such as 3-D image registration. The multiresolution
properties of splines can also be used to construct wavelet bases or frames
with various prescribed properties (e.g. optimal time-frequency
localization).
SESSION SP1:
Medical Imaging: Modalities and Performance
Time: 1:30 pm - 4:30 pm
Lecturer: Oleh Tretiak
Drexel University
Image and signal processing has been a key element in the recent
flourishing of medical imaging technologies. The presentation will review
the modalities in medical imaging, both those in use at present and those
under development. The review will include illustrative examples of x-ray,
nuclear medicine, computer tomography, magnetic resonance imaging, and
ultrasound. New development areas such as impedance tomography and
functional MRI will be described. ROC evaluation of imaging instruments
will be reviewed.
SESSION SP2:
Introduction to Partial Differential Equations in Image Processing
Time: 1:30 pm - 4:30 pm
Lecturer: Jean-Michel Morel
CEREMADE, Universite de Paris 9 Dauphine, France
By considering continuous image representations, most local filtering
operations can be translated into differential operators. The simplest
example is Gaussian smoothing which corresponds to the Laplacian. In the
same way, we shall show that the median filter corresponds to the curvature
of isophotes (iso-level curves), and the dilation operator to the modulus
of the gradient. Iterating such local filters with a neighborhood that
becomes infinitesimally small yields a partial differential equation (PDE).
Thus, any iterative filtering process can be viewed as a partial
differential evolution equation. What is gained by adopting the PDE
methodology ? First, the elementary PDE formalism provides a new and
independent means of classification of iterated filters; certain filters
that appear to be different may have a similar structure that is only
revealed by comparing their underlying PDEs. The formalism also provides a
unification with "scale space" theories. Second, the discretization of
PDE's yields new and more robust ways of implementing classical filters.
Finally, some of the PDE's are new and not necessarily implementable
through discrete filtering, although it is relatively easy to solve then
numerically. The best example of this is the affine-invariant scale space
representation which was discovered using PDE methods. The presentation
will include many such image processing examples and provide a new
viewpoint on several aspects of mathematical morphology.
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