Adapted Total Variation for Artifact Free Decompression of JPEG Images
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The widely used JPEG lossy baseline coding system is known to produce, at low bit rates, blocking effects and Gibbs phenomenon. This paper develops a method to get rid of these artifacts without smoothing images and without removing perceptual features. This results in better looking pictures and improved PSNR. Our algorithm is based on an adapted total variation minimization approach constrained by the knowledge of the input intervals the unquantized cosine coefficients belong to. In this way, we reconstruct an image having the same quantized coefficients than the original one, but which is minimal in term of the total variation. This discourages blocking effects and Gibbs phenomenon to appear while edges are kept as sharp as possible. Although the proposed subgradient method is converging in infinite time, experiments show that best results are obtained with a very few number of iterations. This leads to a simple and fast algorithm that may be applied to the great set of JPEG images to decompress them more efficiently.
Keywordsdeblocking JPEG images total variation image restoration subgradient descent
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