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Cite Details

Rick Chartrand, "Nonconvex regularization for shape preservation", in IEEE International Conference on Image Processing (ICIP), 2007


We show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonly-used total-variation regularization, ∫|∇u|, penalizes the length of object edges. We show that ∫|∇u|p, 0 < p < 1, only penalizes edges of dimension at least 2 - p, and thus finite-length edges not at all. We give numerical examples showing the resulting improvement in shape preservation.

BibTeX Entry

author = {Rick Chartrand},
title = {Nonconvex regularization for shape preservation},
year = {2007},
urlpdf = {http://math.lanl.gov/Research/Publications/Docs/chartrand-2007-nonconvex2.pdf},
booktitle = {IEEE International Conference on Image Processing (ICIP)}