DocumentCode :
1366448
Title :
Blocking-artifact reduction in block-coded images using wavelet-based subband decomposition
Author :
Choi, Hyuk ; Kim, Taejeong
Author_Institution :
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
Volume :
10
Issue :
5
fYear :
2000
fDate :
8/1/2000 12:00:00 AM
Firstpage :
801
Lastpage :
805
Abstract :
We propose a post-processing method in the wavelet transform domain that can significantly reduce the blocking effects in low-bit-rate block-transform-coded images. Although the quantization noise of the transform coefficients is the sole source of error in a coded image, the properties of block transform make the errors appear in two categories: blocky noise, which causes blocking effects, and granular (nonblocky) noise. Noting that subband coding does not suffer from blocky noise, the proposed technique is designed to work in the subband domain. Once a coded image is decomposed into subbands by wavelet filters, most energy of the blocky noise exists on the predetermined block boundaries of their corresponding subbands. We can reduce the blocky noise by a linear minimum mean square error filter, which fully exploits the characteristics of the signal and noise components in each subband. After the blocky noise is reduced, the granular noise can further be decreased by exploiting its nonstructuredness. Computer simulations show that the proposed method visibly reduces the blocking effects in reconstructed images and yields better PSNR improvement
Keywords :
data compression; filtering theory; image coding; image reconstruction; least mean squares methods; noise; quantisation (signal); transform coding; wavelet transforms; LMMSE filter; PSNR; block transform; block-transform-coded images; blocking effects; blocking-artifact reduction; blocky noise; computer simulations; error source; granular noise; linear minimum mean square error filter; low bit rate coded images; noise components; nonblocky noise; post-processing method; quantization noise; reconstructed images; subband coding; subband domain; transform coefficients; wavelet filters; wavelet transform domain; wavelet-based subband decomposition; Discrete cosine transforms; Filtering; Gaussian noise; Mean square error methods; Noise reduction; Nonlinear filters; PSNR; Quantization; Wavelet domain; Wavelet transforms;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/76.856457
Filename :
856457
Link To Document :
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