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A Unified Statistical and Information Theoretic Framework for Multi-modal Image Registration

dc.date.accessioned2004-10-08T20:43:13Z
dc.date.accessioned2018-11-24T10:21:43Z
dc.date.available2004-10-08T20:43:13Z
dc.date.available2018-11-24T10:21:43Z
dc.date.issued2004-04-28en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6738
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/6738
dc.description.abstractWe formulate and interpret several multi-modal registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the "auto-information function", as a means of assessing and exploiting the common spatial dependencies inherent in multi-modal imagery. We analytically derive useful properties of the "auto-information" as well as verify them empirically on multi-modal imagery. Among the useful aspects of the "auto-information function" is that it can be computed from imaging modalities independently and it allows one to decompose the search space of registration problems.en_US
dc.format.extent21 p.en_US
dc.format.extent2760680 bytes
dc.format.extent531001 bytes
dc.language.isoen_US
dc.subjectAIen_US
dc.subjectregistrationen_US
dc.subjectinformation theoryen_US
dc.subjectunified frameworken_US
dc.titleA Unified Statistical and Information Theoretic Framework for Multi-modal Image Registrationen_US


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