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dc.contributor.authorMingolla, Ennioen_US
dc.contributor.authorRoss, Williamen_US
dc.contributor.authorGrossberg, Stephenen_US
dc.date.accessioned2011-11-14T19:07:58Z
dc.date.available2011-11-14T19:07:58Z
dc.date.issued1998-01
dc.identifier.urihttps://hdl.handle.net/2144/2366
dc.description.abstractA neural network system for boundary segmentation and surface representation, inspired by a new local-circuit model of visual processing in the cerebral cortex, is used to enhance images of range data gathered by a synthetic aperture radar (SAR) sensor. Boundary segmentation is accomplished by an improved Boundary Contour System (BCS) model which completes coherent boundaries that retain their sensitivity to image contrasts and locations. A Feature Contour System (FCS) model compensates for local contrast variations and uses the compensated signals to diffusively fill-in surface regions within the BCS boundaries. Image noise pixels that arc not supported by BCS boundaries are hereby eliminated. More generally, BCS/FCS processing normalizes input dynamic range, reduces noise, and enhances contrasts between surface regions. BCS /FCS processing hereby makes structures such as motor vehicles, roads, and buildings more salient to human observers than in original imagery. The new BCS model improves image enhancement with significant reductions in processing time and complexity over previous BCS applications. The new system also outperforms several established techniques for image enhancement.en_US
dc.description.sponsorshipDefense Advanced Research Projects Agency and Office of Naval Research (N00014-95-1-0409); Office of Naval Research (N00014-94-1-0597, N00014-91-J-4100, N00014-95-1-0657); Air Force Office of Scientific Research (90-0175); British Petroleum (BP 89A-1204); HNC Software Inc. (SC-94-001); National Science Foundation (IRI-90-00530, IRI-97-20333)en_US
dc.language.isoen_US
dc.publisherBoston University Center for Adaptive Systems and Department of Cognitive and Neural Systemsen_US
dc.relation.ispartofseriesBUCAS/CNS Technical Reports; BUCAS/CNS-TR-1998-032
dc.rightsCopyright 1998 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.en_US
dc.subjectSynthetic aperture radaren_US
dc.subjectNeural networksen_US
dc.subjectImage enhancementen_US
dc.subjectBoundary segmentationen_US
dc.subjectDiffusionen_US
dc.titleA Neural Network for Enhancing Boundaries and Surfaces in Synthetic Aperture Radar Imagesen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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