Fast Convolutional Sparse Coding (FCSC)
Convolutional sparse coding remedies the shortcomings of the traditional (patch-based) sparse coding by modeling shift
invariance directly. This yields more parsimonious coding schemes but increases complexity by coupling the coding problem for
neighboring image patches where they overlap. Here we describe an optimization approach which exploits the separability of
convolution across bands in the frequency domain in order to make dictionary learning efficient. Our presentation follows the
notation in the paper of [Bristow et al. IEEE CVPR 2013] but includes additional implementation details and corrects some
inaccuracies and typos.
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Text Reference
Bailey Kong and Charless C. Fowlkes. Fast convolutional sparse coding (fcsc). Technical Report, UC Irvine, 2014.BibTeX Reference
@TechReport{KongF_TR_2014,author = "Kong, Bailey and Fowlkes, Charless C.",
title = "Fast Convolutional Sparse Coding (FCSC)",
institution = "UC Irvine",
year = "2014"
}