A Bayesian Iterative Postprocessing Algorithm for DWT-Based Compressed Image

In this paper, a new postprocessing method based on Bayesian theory is proposed to alleviate the blurring effect and remove the ringing effect of a compressed image. Different from traditional method, blurring effect is considered especially at low bit-rate. The compression is equivalent to the blurring processing followed by adding bias, based on which the new postprocessing model is established. An iterative solution is proposed after proper simplification and the parameter selection is discussed. At last, lots of numerical experiments are performed, and the results show that both the subjective perceived quality and the objective evaluation are improved.