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oai:www.ideals.illinois.edu:2142/81187 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

2015-09-25T20:09:59Z 10000-01-01 1997 1997 Bresler, Yoram Kerfoot, Ian B. 2015-09-25T20:09:59Z All MRF image-segmentation criteria as in Step 3 have spatial-penalty parameters that must be chosen. An adaptive algorithm that chooses the penalty parameters to maximize the pseudo-likelihood (PL) of the current image was developed by Lakshmanan and Derin, but it uses a costly simulated-annealing algorithm. We use a decoupling argument to find simple, closed-form solutions for the PL penalty parameters of a globally adaptive (GA) MRF criterion with boundary and region penalties. A theoretical analysis shows that GA penalties only minimize the error rate if the scene has certain weak symmetry properties. For example, all boundaries must be equally rough. This is not always satisfied in practice, so we also introduce an MRF with class-pair-conditional (CP) boundary penalties. We segment both synthetic and real images to validate the theoretical analysis and illustrate the capabilities and limitations inherent to the PL approximation. Made available in DSpace on 2015-09-25T20:09:59Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9737156.pdf: 5492317 bytes, checksum: 5129875f2f872723a9e946d3f129aeef (MD5) Previous issue date: 1997 Embargo set by: Seth Robbins for item 82468 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 189 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997. http://hdl.handle.net/2142/81187 (MiAaPQ)AAI9737156 eng Engineering, Electronics and Electrical Mdl-Based Band Selection and Adaptive Penalties for Hyperspectral Image Segmentation text Electrical Engineering Electrical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.