DocumentCode :
3770283
Title :
Rate-distortion based sparse coding for image set compression
Author :
Xinfeng Zhang;Weisi Lin;Siwei Ma;Shiqi Wang;Wen Gao
Author_Institution :
Rapid-Rich Object Search (ROSE) Lab, Nanyang Technological University, Singapore
fYear :
2015
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, we propose a novel image set compression approach based on sparse coding with an ordered dictionary learned from perceptually informative signals. For a group of similar images, one representative image is first selected and transformed into wavelet domain, and then its AC components are utilized as samples to train an over-complete dictionary. In order to improve compression efficiency, the dictionary atoms are reordered according to their frequency used in sparse approximation of the representative image. In addition, a rate-distortion based sparse coding method is proposed to distribute atoms among different image patches adaptively. Experimental results show that the proposed method outperforms JPEG and JPEG2000 up to 6+ dB and 2+ dB, respectively.
Keywords :
"Image coding","Dictionaries","Distortion","Matching pursuit algorithms","Rate-distortion","Transform coding","Redundancy"
Publisher :
ieee
Conference_Titel :
Visual Communications and Image Processing (VCIP), 2015
Type :
conf
DOI :
10.1109/VCIP.2015.7457891
Filename :
7457891
Link To Document :
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