A Mathematical Framework for Image Analysis
{'Code': '03040109', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Alvin I. Thaler', 'PO_EMAI': None, 'PO_PHON': None}
The proposed research is aimed at the development and at                   the application of a mathematical framework for image analysis.                 The approach is through a Bayesian paradigm.  The presumption                   is that properly conceived prior distribution on relevant scene                 attributes can be an effective basis for image processing.                      Applications are to texture segmentation and classification,                    boundary detection, computerized tomography, and global image                   analysis.
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[{'Code': '1269', 'Text': 'STATISTICS'}, {'Code': '1271', 'Text': 'COMPUTATIONAL MATHEMATICS'}, {'Code': '4720', 'Text': 'SIGNAL PROCESSING SYS PROGRAM'}, {'Code': '6840', 'Text': 'ROBOTICS'}]
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