DocumentCode :
2929867
Title :
An image compression method using sparse representation and grey relation
Author :
Hong-jun Li ; Zheng-Guang Xie ; Wei Hu
Author_Institution :
Sch. of Electron. Inf. Eng., Nantong Univ., Nantong, China
fYear :
2013
fDate :
15-17 Nov. 2013
Firstpage :
53
Lastpage :
56
Abstract :
Traditional wavelet transform needs to be improved and perfected in sparse representation. In this paper, we proposed an image compression algorithm based on grey relational theory in wavelet domain. We use the character of wavelet coefficients, and apply the grey relational theory in coefficients relational description, and then propose an image compression method via grey relational theory. We classify the coefficients according to their characters in different domains and construct the sparse representation method under different types of coefficients. The algorithm reduces the computational complexity and improves the ability of image sparse representation. It achieves an efficient way of image compression. The simulation results show that the proposed compression algorithm based on grey relational theory is superior to the other algorithms both in the visual quality and PSNR.
Keywords :
data compression; grey systems; image coding; wavelet transforms; PSNR; computational complexity; grey relational theory; image compression method; image sparse representation; sparse representation; wavelet coefficients; wavelet domain; Correlation; Dictionaries; Image coding; PSNR; Wavelet coefficients; grey relational theory; image compression; image sparse representation; wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grey Systems and Intelligent Services, 2013 IEEE International Conference on
Conference_Location :
Macao
ISSN :
2166-9430
Print_ISBN :
978-1-4673-5247-5
Type :
conf
DOI :
10.1109/GSIS.2013.6714741
Filename :
6714741
Link To Document :
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