Color Affine Subspace Pursuit for Color Artifact Removal

Abstract

This paper proposes color affine subspace pursuit (CASSP) for color artifact removal. Local patches in natural color images tend to exhibit a line distribution, so-called a color line. According to this characteristic, a convex-optimization-based image recovery with a local color nuclear norm (LCNN) has conventionally been introduced to promote the color line property of local patches and succeeded in removing color artifacts. It is, however, often the case that a local patch does not form a line distribution, but a union of affine subspaces (UoAS), e.g., a patch consisting of two different colors. In such regions, the LCNN often results in color fading or color smearing. This paper promotes the UoAS property, i.e., the color line or plane distribution for each affine subspace in local patches by using CASSP. Our cost function for the CASSP consists of the LCNN for each centered color distribution cluster. Experimental results show that the CASSP improves both numerical reconstruction error and subjective visual quality, compared with the LCNN.