Improved algorithm for image inpainting based on clustering segmentation and texture synthesis
Xiao Jua · Computer Engineering and Applications Journal · 2014
Criminisi proposed exemplar-based image inpainting techniques need to traverse the whole image exemplar, it is too costly, and may choose the wrong exemplar, constantly updates iteration error messages resulting cumulative, so that a greater deviation may be in inpainting results. Meanwhile, considering the Criminisi algorithm priority function calculation may lead to a structural distortion in inpainting results, which proposes an improved algorithm for image inpainting based on clustering segmentation and texture synthesis, the search will be limited to the same categories zone with the source exemplar covered. In the pixel priority calculation, the pixel neighborhood gray gradient difference information is introduced, the priority of more reasonable formula is proposed to ensure maximum edge preferentially transmitted in complex scenes and update entries in confidence difference to treat newly filled pixels. The experimental results show that the improved algorithm not only solves the Criminisi algorithm possible continuation of structural bias problem, repairing the visual effect is more in line with people's subjective feelings, but also greatly shortens the repair time.