Title :
Compressive Sensing of Noisy Multispectral Images
Author :
Peng Liu ; Eom, Kie B.
Author_Institution :
Inst. of Remote Sensing & Digital Earth, Beijing, China
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;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2014.2314177