DocumentCode :
2820069
Title :
L2 restoration of L-decoded images with context modeling
Author :
Zhou, Jiantao ; Wu, Xiaolin
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
1989
Lastpage :
1992
Abstract :
The L-constrained image coding is a technique to achieve substantially lower bit rate than strictly (mathematically) lossless image coding while still imposing a tight error bound at each pixel (colloquially referred to as near-lossless image coding). However, this technique becomes inferior in the L2 distortion metric if the bit rate decreases further. We propose a new soft decoding approach to reduce the L2 distortion of L-coded images, benefiting from the advantages of both minmax and mean square approximations. This is made possible by context modeling of quantization distortions and by exploiting the L bound inherent to near-lossless coding in a framework of image restoration. In addition, the proposed soft decoding approach offers an asymmetric high-fidelity image compression solution: the encoder is of low complexity with heavy computations of gaining coding efficiency performed by the decoder. Experimental results demonstrate that the new soft decoding approach can improve the PSNR of L-decoded images by more than 1 dB, and it can even outperform JPEG 2000 (a state-of-the-art encoder-optimized image codec) for bit rates higher than 1.17 bpp, while achieving much tighter L error bound.
Keywords :
data compression; distortion; image coding; image restoration; mean square error methods; minimax techniques; quantisation (signal); JPEG 2000; L constrained image coding; L error bound; PSNR; context modeling; distortion metric; image compression; image restoration; lossless image coding; mean square approximations; minmax technique; quantization distortions; soft decoding approach; Bit rate; Decoding; Image coding; Image restoration; PSNR; Transform coding; Near-lossless image compression; context modeling; estimation; image restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
ISSN :
1522-4880
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2011.6115865
Filename :
6115865
Link To Document :
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