Image Texture Removal by Total Variantional Rolling Guidance

The image texture removal is a solution for the image content separation problem, which aim at preserving image edges and removing uninterested textures. This problem has wide applications in image feature extractions, such as texture extraction, detail enhancement and so on. A new image content decomposition approach is introduced with a minimization refinement architecture in this paper, which contains the guidance component and the total varation component. The guidance component introduces a rolling guidance filtering to iteratively update the more and more smoothing images. The total varation component uses a new total variation regularization method to remove the image texture and preserve the structural contents. The non-convex objective function is simplified into these two sub-problems, which yield a linear solution. Then the experiments demonstrate the prior performance of our method and its potential for many image processing applications.