Image Inpainting Considering Brightness Change and Spatial Locality of Textures and Its Evaluation
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Image inpainting with a learned guidance vector field
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
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In this paper we propose a novel technique to image completion that addresses image renaissance through a graph-based matching process. To this end, a number of candidate seeds with content similar to the one of the area to be inpainted are considered. They are selected through a particle filter method and then positioned over the missing area. Markov Random Fields are used to formalize inpainting as a labeling estimation problem while a combinatorial approach is used to recover the optimal partition of patches that completes the missing area with the á-expansion process. Promising results in image and texture completion demonstrate the potentials of the proposed method.