Image recovery from partial wavelet coefficients via sparse representation
Authors: 
Georgin Jacob, C. V. JijiAuthors Info & Claims
Georgin Jacob, C. V. JijiAuthors Info & ClaimsArticle No.: 63, Pages 1 - 8
Abstract
Loss of information in wavelet transform domain may occur while transmitting images represented in JPEG 2000. This produces artifacts like black holes, degraded edges and correlated damage patterns in received images. Recovering an image from its partial wavelet coefficients or filling the missing wavelet coefficients from the available coefficients is called wavelet inpainting. This problem is closely related to image inpainting but here inpainting is done in wavelet domain. Mathematically it is equivalent to solving a set of under determined system of equations having infinite number of solutions. In this paper, we propose an efficient algorithm that uses greedy Orthogonal Matching Pursuit (OMP) algorithm that solves the under determined problem by minimizing the l0 norm of the sparse Discrete Cosine Transform (DCT) representation of the image. The image is reconstructed by taking inverse DCT. We show that good quality reconstruction can be obtained even if 50 % of the randomly selected wavelet coefficients including the approximation coefficients are missing. The proposed method outperforms the gradient based and optimum transfer function based inpainting algorithms in terms of SNR.
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- Image recovery from partial wavelet coefficients via sparse representation
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Published: 16 December 2012
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ICVGIP '12
ICVGIP '12: The Eighth Indian Conference on Vision, Graphics and Image Processing
December 16 - 19, 2012
Mumbai, India
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