Accession Number : ADA266772


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


Descriptive Note : Final rept. 15 Jan 90-14 Jan 93,


Corporate Author : BROWN UNIV PROVIDENCE RI


Personal Author(s) : Gidas, Basilis


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a266772.pdf


Report Date : 15 Apr 1993


Pagination or Media Count : 10


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.


Descriptors :   *IMAGE PROCESSING , ALGORITHMS , PARAMETERS , MAXIMUM LIKELIHOOD ESTIMATION , GRIDS , SHAPE , TERRAIN , CODING , THREE DIMENSIONAL , LENGTH , IMAGES , CLASSIFICATION , SPEECH RECOGNITION , MAPS , SPEECH , TOMOGRAPHY , TEXTURE , TOPOGRAPHIC MAPS


Subject Categories : Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE