Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/LGRS.2014.2314177 | IEEE Geosci. Remote Sensing Lett. |
Keywords | Field | DocType |
remote sensing,image processing,transform domains,bregman split method,compressive sensing,spatial domains,compressed sensing,optimization,remote sensing applications,regularization,noisy multispectral images,multispectral,psnr,image reconstruction,principal component analysis,noise measurement | Iterative reconstruction,Computer vision,Noise measurement,Pattern recognition,Remote sensing,Multispectral image,Remote sensing application,Multispectral pattern recognition,Artificial intelligence,Mathematics,Compressed sensing,Principal component analysis | Journal |
Volume | Issue | ISSN |
11 | 11 | 1545-598X |
Citations | PageRank | References |
7 | 0.49 | 12 |
Authors | ||
2 | ||