Saliency-Based Compressive Sampling for Image Signals

  title={Saliency-Based Compressive Sampling for Image Signals},
  author={Ying Yu and Bin Wang and Liming Zhang},
  journal={IEEE Signal Processing Letters},
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… CONTINUE READING
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