A practical projection-based postprocessing of block-coded images with fast convergence rate

At present, block-transform coding is probably the most popular approach fo r image compression. However, for the sake of its implementation, an image is partitioned into spatially adjoining blocks which are processed independ ently without considering inter-block correlation. So, this approach inesca pably causes an annoying defect called a blocking artifact. In this letter, in order to reduce a blocking artifact appearing in block-coded images, a new quantization constraint set based on the theory of projection onto conv ex set (POCS) is proposed. This set can efficiently complement the drawback s of the projection onto the other constraint sets, particularly the smooth ness constraint set, Experimental results, using the proposed quantization constraint set as a substitute for the conventional quantization constraint set, show that the postprocessed images not only converge at a fast rate b ut also obtain better performance in both objective and subjective quality, Moreover, we know that the postprocessed images maintain the clearness of the decoded image before postprocessing.