一种基于稀疏正则化的图像盲复原方法

doi:10.3969/j.issn.1001-2400.2012.06.027

Abstract

Abstract:

In the process of image blind deconvolution, the main obstacle is the lack of enough information about the point spread function (PSF), which leads to the ill-posed problem. To solve this problem, we can give regularization constraints on the original image and PSF simultaneously. In order to gain the stable and unique solution and guarantee the effectiveness of the resulting image restoration, this paper uses a scale invariant and sparse regularization function, and experiments are conducted to verify that our image blind recovery algorithm is robust and has stable convergence.

Key words: image blind restoration, sparse representation, deconvolution

WANG Shuzhen;ZOU Zijian;LI Li;ZHANG Xiaoping. Method for blind image restoration based on sparse regularization[J].J4, 2012, 39(6): 167-169+186.

References

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Method for blind image restoration based on sparse regularization

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