Sparse coding image denoising based on saliency map weight

Authors:
Haohua Zhao;Liqing Zhang
Affiliations:
MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Year:
2011

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Abstract

Saliency maps provide a measurement of people's attention to images. People pay more attention to salient regions and perceive more information in them. Image denoising enhances image quality by reducing the noise in contaminated images. Here we implement an algorithm framework to use a saliency map as weight to manage tradeoffs in denoising using sparse coding. Computer simulations confirm that the proposed method achieves better performance than a method without the saliency map.