Matching Pursuit Based Convolutional Sparse Coding

Elad Plaut; Raja Giryes

ICASSP 2018accepted0 citations

Matching Pursuit Based Convolutional Sparse Coding

Abstract

Convolutional sparse coding using the ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0,∞</sub> norm has been described as “a problem that operates locally while thinking globally”. In this paper, we present a matching pursuit based greedy algorithm specifically tailored to the ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0,∞</sub> norm. We also propose a corresponding dictionary learning algorithm, which trains a local dictionary on a set of global images. Our approach is based on the convolutional relationship between the local dictionary and the global image. It operates locally while taking into account the global nature of the images. We demonstrate the usage of our proposed strategy for the task of image inpainting.

BibTeX

@inproceedings{icassp2018_matchingpursuitb,
  title = {Matching Pursuit Based Convolutional Sparse Coding},
  author = {Elad Plaut and Raja Giryes},
  booktitle = {ICASSP 2018},
  year = {2018}
}