ICASSP 2018accepted0 citations

L1 Patch-Based Image Partitioning into Homogeneous Textured Regions

Maria Oliver, Gloria Haro, Vadim Fedorov, Coloma Ballester

Abstract

This paper proposes a novel patch-based variational segmentation method that considers adaptive patches to characterize, in an affine invariant way, the local structure of each homogeneous texture region of the image and thus being capable of grouping the same kind of texture regardless of differences in the point of view or suffered perspective distortion. The patches are computed using an affine covariant structure tensor defined at every pixel of the image domain, so that they can automatically adapt its shape and size. They are used in a segmentation model that uses an L <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> -norm fidelity term and fuzzy membership functions, which is solved by an alternating scheme. The output of the method is a partition of the image in regions with homogeneous texture together with a patch representative of the texture of each region.

BibTeX
@inproceedings{icassp2018_l1patchbasedimag,
  title = {L1 Patch-Based Image Partitioning into Homogeneous Textured Regions},
  author = {Maria Oliver and Gloria Haro and Vadim Fedorov and Coloma Ballester},
  booktitle = {ICASSP 2018},
  year = {2018}
}