A new algorithm of projection onto narrow quantization constraint set for postprocessing of quantized images

In this paper, we propose a new method to reduce coding artifacts in transform image coding. It consists of a filtering scheme in spatial domain followed by a new projection algorithm onto the narrow quantization constraint set (NQCS). Generally, the projection onto NQCS can provide a better performance in terms of PSNR than the projection onto the conventional QCS. When the value of the narrowing factor is low, however, the projection onto NQCS does not guarantee a better performance, because it projects the transform coefficients that lie inside of the Original QCS onto NQCS. The proposed method projects transform coefficients that lie only outside of the original QCS onto the NQCS. Different projection methods are used for AC and DC coefficients, because the characteristics of distribution are different. The PSNR improvement ranges between 0.7 and 1.4 dB, compared with the decoded images without postprocessing. The PSNR gain of 0.2 to 0.5 dB is obtained, compared with the conventional projection method onto the NQCS.