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Proceedings Paper

An adaptive total variation model with local constraints for denoising partially textured images
Author(s): A. A. Bini; M. S. Bhat; P. Jidesh
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Paper 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.

Paper Details

Date Published: 30 September 2011
PDF: 7 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828528 (30 September 2011); doi: 10.1117/12.913494
Show Author Affiliations
A. A. Bini, National Institute of Technology (India)
M. S. Bhat, National Institute of Technology (India)
P. Jidesh, National Institute of Technology (India)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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