DocumentCode
87763
Title
Compressive Sensing of Noisy Multispectral Images
Author
Peng Liu ; Eom, Kie B.
Author_Institution
Inst. of Remote Sensing & Digital Earth, Beijing, China
Volume
11
Issue
11
fYear
2014
fDate
Nov. 2014
Firstpage
1931
Lastpage
1935
Abstract
Compressive sensing of noisy multispectral images is considered in this letter. Multispectral images in remote sensing applications are multichannel and inherently noisy. An approach using Bregman split method for optimization in both spatial and transform domains is proposed. The performance of the proposed algorithm is evaluated by comparing with other approaches. It is shown that the proposed algorithm performs favorably compared with other approaches with noisy multispectral images in experiments.
Keywords
compressed sensing; image processing; remote sensing; Bregman split method; compressive sensing; noisy multispectral images; optimization; remote sensing applications; spatial domains; transform domains; Compressed sensing; Image reconstruction; Noise measurement; PSNR; Principal component analysis; Transforms; Compressive sensing; multispectral; regularization; remote sensing;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2014.2314177
Filename
6803045
Link To Document