Image structure rebuilding technique using fractal dimension on the best match patch searching

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• 作者：Jung-San Lee ; Kuo-Jui Wei ; Kai-Rui Wen
• 关键词：Inpainting ; Fractal dimension ; Sparsity ; Structure
• 刊名：Multimedia Tools and Applications
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：76
• 期：2
• 页码：1875-1899
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems;
• 出版者：Springer US
• ISSN：1573-7721
• 卷排序：76

文摘

Since most images were built with regular textures and structures, the exemplar-based inpainting technique has become a brand-new solution for renovating degraded images by searching a match patch. This characteristic has also been named as the local self-similarity. Nevertheless, traditional exemplar-based methods try to find the best match patch in the whole image with only one direction; thus, often leading to a non-ideal repairing result. In this article, we propose a novel patch matching technique to rebuild the structure and texture of image, in which the surrounding information of the patch is fully concerned. Aside from determining a more precise filling priority by the sparsity of the image structure, we have applied the difference of fractal dimension to enhance the similarity between the source patch and the target patch. Experimental results have demonstrated the superiority of the proposed technique over related works in the renovating accuracy.