Multiresolution Methods in Systems, Signals and Images
Final rept. 1 Dec 94-28 Feb 98
MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS
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In this final report we summarize our research accomplishments under this grant a research on our multiresolution estimation methodology to solve a variety of difficult image and large scale data assimilation problems and to extend the theoretical domain of applicability of our methodology considerably to allow for the fusion of multisensor data b the development of several new methods involving synthetic aperture radar SAR data including multiresolution segmentation and compression algorithms and an estimation-theoretic approach to moving target SAR image formation c the development of a new nonlinear multiresolution image evolution algorithm that produces extremely robust image segmentations d the development of a new variation on so-called matching pursuit methods with application to robust and stable feature extraction and recognition of objects and e the development of hierarchical and wavelet-based methods for the design of joint detection algorithms for multiple access communication in the presence of highly correlated user signals. In addition a number of significant transitions and interactions resulting from our work are described.
- Active and Passive Radar Detection and Equipment