An adaptive total variation model with local constraints for denoising partially textured images

A. A. Bini; M. S. Bhat; P. Jidesh

doi:10.1117/12.913494

30 September 2011 An adaptive total variation model with local constraints for denoising partially textured images

A. A. Bini, M. S. Bhat, P. Jidesh

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 828528 (2011) https://doi.org/10.1117/12.913494
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

Abstract

Denoising algorithms such as Total Variation model modify smooth areas in images into piecewise constant patches and small scale details and textures present in the original image are not preserved satisfactorily by these processes. In this paper, we present an algorithm based on an adaptive Total Variation norm of the gradient of the image, with a family of local constraints for efficient denoising of natural images. In fact, natural images consist of smooth and textured regions. Staircase effect is reduced in smooth areas by using a modified Total Variation functional. The set of local constraints, one for each pixel in the image are able to preserve most of the fine details and textures in the images. Visual and quantitative results of proposed method are presented and are compared with results of existing methods.

Citation Download Citation

A. A. Bini, M. S. Bhat, and P. Jidesh "An adaptive total variation model with local constraints for denoising partially textured images", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828528 (30 September 2011); https://doi.org/10.1117/12.913494

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