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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5601| Title: | Learning a Color Algorithm from Examples |
| Keywords: | computer vision color constancy learning regularization soptimal estimation pseudoinverse |
| Issue Date: | 9-Oct-2013 |
| Description: | We 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. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-909 http://hdl.handle.net/1721.1/5601 |
| Appears in Collections: | MIT Items |
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