Title: The Examplar-based Image Inpainting algorithm through Patch Propagation
Abstract:The filling-in of missing region in an image, which is Called image inpainting. Image inpainting is a technique for removing undesired objects in images and reconstructing the missing regions in a vis...The filling-in of missing region in an image, which is Called image inpainting. Image inpainting is a technique for removing undesired objects in images and reconstructing the missing regions in a visually plausible way. Recently various approaches have been proposed a large variety of examplar based image inpainting algorithms to restore the structure and texture of damaged images. In this paper we introduce a novel and efficient exemplar based Image Inpainting Algorithm with investigating the sparsity of natural image patches. Two crucial steps of patch propagation are used in the examplar-based inpainting approach. First, to measure the confidence of a patch located at the image structure (e.g., the edge or corner) structure sparsity is designed at patch level. Second, it is assumed that the patch to be filled by the sparse linear combination of candidate patches under the local patch consistency of sparse representation. The patch with larger structure sparsity will be assigned higher priority for further inpainting. An improved priority term defines the filling order of patches in the image. In the proposed approach, Structure sparsity provides better discrimination of structure and texture, and the patch sparse representation forces the newly inpainted regions to be sharp and consistent with the surrounding textures.Read More
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
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Cited By Count: 3
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