DocumentCode :
2816114
Title :
On sparse representations of color images
Author :
Wu, Xiaolin ; Zhai, Guangtao
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
1229
Lastpage :
1232
Abstract :
We investigate an intrinsic and useful form of sparsity of color images that was largely overlooked in the literature of image/video processing. This sparsity of multispectral images is revealed and formulated by modeling the image formation process. The underlying new sparse representations of color images are general and can be exploited to improve the performance of existing image restoration algorithms, such as denoising, deblurring, and resolution upconversion.
Keywords :
image colour analysis; image representation; image restoration; inverse problems; color images; image processing; image restoration algorithms; inverse problem; multispectral images; sparse representations; video processing; Color; Deconvolution; Image restoration; Materials; Noise reduction; Surface waves; Sparse representations of images; image formation model; image restoration; inverse problem;
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.2011.6115654
Filename :
6115654
Link To Document :
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