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Image fusion using sparse overcomplete feature dictionaries

United States Patent

9,152,881
October 6, 2015
View the Complete Patent at the US Patent & Trademark Office
Los Alamos National Laboratory - Visit the Technology Transfer Division Website
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.
Brumby; Steven P. (Santa Fe, NM), Bettencourt; Luis (Los Alamos, NM), Kenyon; Garrett T. (Santa Fe, NM), Chartrand; Rick (Los Alamos, NM), Wohlberg; Brendt (Los Alamos, NM)
Los Alamos National Security, LLC (Los Alamos, NM)
14/ 026,295
20140072209
September 13, 2013
STATEMENT OF FEDERAL RIGHTS The United States government has rights in this invention pursuant to Contract No. DE-AC52-06NA25396 between the United States Department of Energy and Los Alamos National Security, LLC for the operation of Los Alamos National Laboratory.