DocumentCode :
1335753
Title :
Saliency-Based Compressive Sampling for Image Signals
Author :
Yu, Ying ; Wang, Bin ; Zhang, Liming
Author_Institution :
Dept. of Electron. Eng., Fudan Univ., Shanghai, China
Volume :
17
Issue :
11
fYear :
2010
Firstpage :
973
Lastpage :
976
Abstract :
Compressive sampling is a novel framework in signal acquisition and reconstruction, which achieves sub-Nyquist sampling by exploiting the sparse nature of most signals of interest. In this letter, we propose a saliency-based compressive sampling scheme for image signals. The key idea is to exploit the saliency information of images, and allocate more sensing resources to salient regions but fewer to nonsalient regions. The scheme takes human visual attention into consideration because human vision would pay more attention to salient regions. Simulation results on natural images show that the proposed scheme improves the reconstructed image quality considerably compared to the case when saliency information is not used.
Keywords :
image reconstruction; image sampling; image reconstruction; image signals; saliency-based compressive sampling; signal acquisition; signal reconstruction; sub-Nyquist sampling; Discrete cosine transforms; Humans; Image coding; Image reconstruction; Pixel; Sensors; Visualization; Visual saliency; compressive sampling; discrete cosine transform;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2010.2080673
Filename :
5585813
Link To Document :
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