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