A Multilevel-Multiresolution Method for Image Processing. A Bayesian Framework for Reconstructing and Representing Shapes

Abstract

During the period of the grant, 1/15/90 - 1/14/93, we have developed: (1) a coherent multiresolution framework for image analysis tasks, in particular, for estimating 3-D shapes from a single video or SAR image; the algorithm has been applied to constructing topographic maps of Venus' terrain, and to segmentation/classification of textures, (2) efficient procedures for estimating the parameters of Markov Random Fields (MRF's) from noisy and degraded data, (3) a fixed-length noiseless source coding for MRF's using large deviations, and (4) a multi-grid type algorithm for maximum-likelihood estimation in tomography. In addition, we have begun a new non-parametric approach to speech recognition.

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Document Details

Document Type
Technical Report
Publication Date
Apr 15, 1993
Accession Number
ADA266772

Entities

People

  • Basilis Gidas

Organizations

  • Brown University

Tags

Communities of Interest

  • Advanced Electronics
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Bayesian Networks
  • Computational Science
  • Computer Vision
  • Data Science
  • Hidden Markov Models
  • Image Processing
  • Information Processing
  • Markov Models
  • Mathematical Analysis
  • Mathematical Models
  • Models
  • Monte Carlo Method
  • Probability
  • Statistical Inference
  • Three Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms