Image decomposition: separation of texture from piecewise smooth content

Jean-Luc Starck; Mikael Elad; David L. Donoho

doi:10.1117/12.507447

13 November 2003 Image decomposition: separation of texture from piecewise smooth content

Jean-Luc Starck, Mikael Elad, David L. Donoho

Proceedings Volume 5207, Wavelets: Applications in Signal and Image Processing X; (2003) https://doi.org/10.1117/12.507447
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

This paper presents a novel method for separating images into texture and piecewise smooth parts. The proposed approach is based on a combination of the Basis Pursuit Denoising (BPDN) algorithm and the Total-Variation (TV) regularization scheme. The basic idea promoted in this paper is the use of two appropriate dictionaries, one for the representation of textures, and the other for the natural scene parts. Each dictionary is designed for sparse representation of a particular type of image-content (either texture or piecewise smooth). The use of BPDN with the two augmented dictionaries leads to the desired separation, along with noise removal as a by-product. As the need to choose a proper dictionary for natural scene is very hard, a TV regularization is employed to better direct the separation process. Experimental results validate the algorithm's performance.

Citation Download Citation

Jean-Luc Starck, Mikael Elad, and David L. Donoho "Image decomposition: separation of texture from piecewise smooth content", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); https://doi.org/10.1117/12.507447

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