Title: Improvement of Patch Selection in Exemplar-based Image Inpainting
Abstract:In the existing exemplar based image inpainting algorithms, the most similar match patches are used to in-paint the destroyed region, and are searched in the whole source region in a fixed size. Howev...In the existing exemplar based image inpainting algorithms, the most similar match patches are used to in-paint the destroyed region, and are searched in the whole source region in a fixed size. However, sometimes such an approach would decrease the connectivity of structure and clearness of texture while increases the time complexity. To solve these problems, firstly we propose an adaptive sample algorithm based on patch sparsity, by which divide the patch into three types ( smooth type, transition type and edge type ). Then the size of the sample patch can be adaptively changed according to the type. Secondly a candidate patch method is also proposed to improve the patch matching performance. Simulation results show that the proposed method obtains a more reasonable patches than the traditional one. Furthermore, it gives a better texture inpainting effect, especially when the processed image either has the complex and regular textures or has a large destroyed region.Read More
Publication Year: 2015
Publication Date: 2015-10-25
Language: en
Type: article
Indexed In: ['crossref']
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