Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5601
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dc.creatorHurlbert, Anya-
dc.creatorPoggio, Tomaso-
dc.date2004-10-01T20:10:35Z-
dc.date2004-10-01T20:10:35Z-
dc.date1987-06-01-
dc.date.accessioned2013-10-09T02:40:15Z-
dc.date.available2013-10-09T02:40:15Z-
dc.date.issued2013-10-09-
dc.identifierAIM-909-
dc.identifierhttp://hdl.handle.net/1721.1/5601-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1721-
dc.descriptionWe show that a color algorithm capable of separating illumination from reflectance in a Mondrian world can be learned from a set of examples. The learned algorithm is equivalent to filtering the image data---in which reflectance and illumination are mixed---through a center-surround receptive field in individual chromatic channels. The operation resembles the "retinex" algorithm recently proposed by Edwin Land. This result is a specific instance of our earlier results that a standard regularization algorithm can be learned from examples. It illustrates that the natural constraints needed to solve a problemsin inverse optics can be extracted directly from a sufficient set of input data and the corresponding solutions. The learning procedure has been implemented as a parallel algorithm on the Connection Machine System.-
dc.format30 p.-
dc.format4549310 bytes-
dc.format1641242 bytes-
dc.formatapplication/postscript-
dc.formatapplication/pdf-
dc.languageen_US-
dc.relationAIM-909-
dc.subjectcomputer vision-
dc.subjectcolor constancy-
dc.subjectlearning-
dc.subjectregularization-
dc.subjectsoptimal estimation-
dc.subjectpseudoinverse-
dc.titleLearning a Color Algorithm from Examples-
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