Haohao Song, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China
Songyu Yu, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China
Chen Wang, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China
Li Song, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China
Hongkai Xiong, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China
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.
Citation:
Haohao Song, Songyu Yu, Chen Wang, Li Song, Hongkai Xiong, "A New Deblocking Algorithm Based on Adjusted Contourlet Transform," icme, pp.449-452, 2006 IEEE International Conference on Multimedia and Expo, 2006
PURCHASE ARTICLE: $19
IEEE Xplore Subscribers
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb