图像修复问题的低秩对偶逼近算法

doi:10.3969/j.issn.1001-2400.2016.04.030

Abstract

Abstract:

A novel image inpainting algorithm is proposed to improve the traditional exemplar-based inpainting methods. The new approach uses a salient-based ranking method to ensure the priority of the target patch with structure edges, whose similar exemplars would be measured by the image Euclidean distance. And a low-rank and dual approximation of the selected exemplar matrix is used to extract the available information for inpainting. Experimental results show that the new algorithm preferentially repairs significant structures accurately, and performs well in different kinds of missing or damaged cases.

Key words: image restoration, edge detection, image Euclidean distance, approximation theory

FENG Xiangchu;WANG Siqi;LI Xiaoping. Low-rank and dual approximation method for image inpainting problems[J].Journal of Xidian University, 2016, 43(4): 172-177.

References

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Low-rank and dual approximation method for image inpainting problems

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