Multiscale AM-FM image reconstructions based on elastic net regression and Gabor filterbanks
PublisherIEEE Computer Society
SourceConference Record - Asilomar Conference on Signals, Systems and Computers
2013 47th Asilomar Conference on Signals, Systems and Computers
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The paper proposes the use of elastic net regression for reconstructing images from AM-FM components. Current AM-FM reconstruction methods are based on Dominant Component Analysis (DCA), multi-scale DCA, and Channel Component Analysis (CCA). The paper introduce a variation on CCA that uses elastic net regression to minimize the number of channels that are used in the reconstruction. The new approach is validated using a family of Gabor filterbanks that is parameterized by an overlap index. The results show that the elastic net regression component selection algorithm performs significantly better than multiscale DCA. © 2013 IEEE.