Nonconvex Regularization for Shape Preservation
Rick Chartrand · Proceedings - International Conference on Image Processing · 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, int |nablau|, penalizes the length of object edges. We show that int |nablau|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.