DocumentCode
3515552
Title
Image deblocking using dual adaptive FIR Wiener filter in the DCT transform domain
Author
Zhang, Renqi ; Ouyang, Wanli ; Cham, Wai-Kuen
Author_Institution
Dept. of EE, Chinese Univ. of Hong Kong, Hong Kong
fYear
2009
fDate
19-24 April 2009
Firstpage
1181
Lastpage
1184
Abstract
Blocking artifacts exist in images and video sequences compressed to low bit rates using block discrete cosine transform (DCT) compression standards. In order to reduce blocking artifacts, a novel DCT domain technique is presented in this paper. Firstly, a new FIR Wiener filter which exploits the dependence of neighboring DCT coefficients based on the linear minimum mean-square-error (LMMSE) criterion is proposed. Then we apply the new FIR Wiener filter twice in a dual adaptive filtering structure to restore each quantized DCT coefficient. In addition, an efficient parameter estimation method is proposed for the designed filter. Experimental results show that the performance of the proposed method is comparable to the state-of-the-art methods but has low computational complexity.
Keywords
FIR filters; Wiener filters; adaptive filters; computational complexity; discrete cosine transforms; image sequences; mean square error methods; block discrete cosine transform compression; computational complexity; dual adaptive FIR Wiener filter; image deblocking; image sequences; linear minimum mean-square-error criterion; video sequences; Adaptive filters; Bit rate; Discrete cosine transforms; Discrete transforms; Finite impulse response filter; Image coding; Image restoration; Parameter estimation; Video sequences; Wiener filter; Blocking artifacts; DCT coefficient; FIR Wiener filter; dual adaptive filtering; parameter estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4959800
Filename
4959800
Link To Document