A New Deblocking Algorithm Based on Adjusted Contourlet Transform

Abstract

A new postprocessing method based on adjusted contourlet transform is introduced in this paper for suppressing blocking artifacts (BA) in block-based discrete cosine transform (BDCT) compressed images. To our best knowledge, this is the first time contourlet is applied to this field. By exploiting scale space edge detector (ss-edge detector), our algorithm can extract and protect blocking map (BM) and edge map (EM) in the compressed image respectively in the same time. By transforming the compressed image into adjusted contourlet domain, the adaptive thresholds are obtained according to BM. According to the adaptive thresholds, the contourlet coefficients in different subbands are filtered. Experimental results show that our deblocking algorithm achieves better performance than the other iterative and noniterative methods reported in the literature.

Publication
2006 IEEE International Conference on Multimedia and Expo
Li Song
Li Song
Professor, IEEE Senior Member

Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.