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