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Blocking-Artifact Reduction using Projection onto Adaptive Quantization Constraint Set  

정연식 (성공회대학교 컴퓨터정보공학부)
김인겸 (성결대학교 정보통신공학부)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.40, no.1, 2003 , pp. 79-86 More about this Journal
Abstract
A new quantization constraint set based on the theory of Projection onto Convex Set(POCS) is proposed to reduce blocking artifact appearing in block-coded images. POCS-based postprocessing for alleviating the blocking artifact consists of iterative projections onto smoothness constraint set and quantization constraint set, respectively. In general, the conventional quantization constraint set has the maximum size of range where original image data can be included, therefore over-blurring of restored image is unavoidable as iteration proceeds. The projection onto the proposed quantization constraint set can reduce blocking artifact as well as maintain the clearness of the decoded image, since it controls adaptively the size of quantization constraint set according to the DCT coefficients. Simulation results using the proposed quantization constraint set as a substitute for conventional quantization constraint set show that the blocking artifact of the decoded image can be reduced by the small number of iterations, and we know that the postprocessed image maintains the distinction of the decoded image.
Keywords
Projection Onto Convex Set(POCS); Block Region Classification; Adaptive Quantization Constraint Set;
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