Entropy Based Cartoon Texture Separation

TL;DR

This paper presents a novel method for separating cartoon and texture components in images using multi-scale Total-Variation filtering combined with an information-theoretic pixel selection criterion, improving image processing tasks.

Contribution

It introduces a new cartoon-texture separation technique based on multi-scale TV filtering and information theory, differing from traditional energy minimization models.

Findings

Effective separation of cartoon and texture components demonstrated

Improved image segmentation and inpainting results

Enhanced image compression capabilities

Abstract

Separating an image into cartoon and texture components comes useful in image processing applications, such as image compression, image segmentation, image inpainting. Yves Meyer's influential cartoon texture decomposition model involves deriving an energy functional by choosing appropriate spaces and functionals. Minimizers of the derived energy functional are cartoon and texture components of an image. In this study, cartoon part of an image is separated, by reconstructing it from pixels of multi scale Total-Variation filtered versions of the original image which is sought to be decomposed into cartoon and texture parts. An information theoretic pixel by pixel selection criteria is employed to choose the contributing pixels and their scales.