@inproceedings{d69d552cd01f4ae285dc958d876f7810,
title = "Rate-distortion based sparse coding for image set compression",
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 ratedistortion 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 = "dictionary, Image compression, rate-distortion, sparse coding",
author = "Xinfeng Zhang and Weisi Lin and Siwei Ma and Shiqi Wang and Wen Gao",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; Visual Communications and Image Processing, VCIP 2015 ; Conference date: 13-12-2015 Through 16-12-2015",
year = "2015",
doi = "10.1109/VCIP.2015.7457891",
language = "英语",
series = "2015 Visual Communications and Image Processing, VCIP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 Visual Communications and Image Processing, VCIP 2015",
address = "美国",
}