关键词: 图像修复, 曲率驱动扩散模型, 修复精度, 时间复杂度

Abstract: Currently, various image inpainting algorithms based on Curvature-Driven Diffusion (CDD) model only make use of the reference information of four neighborhood pixels. Therefore, they cannot keep shape edges and their inpainting precisions high enough. To conquer these difficulties, the image inpainting algorithm based on double-cross CDD was presented, in which the reference information for damaged pixel was extended from four into eight neighborhood pixels. Firstly, one inpainting value for damaged pixel could obtain from the reference information of four neighborhood pixels using the original CDD algorithm. Secondly, another new inpainting value was computed with the newly introduced four neighborhood pixels. Finally, the final inpainting value was a weighted mean of the above-mentioned two inpainting computational value. The proposed method, original CDD algorithm and its improved editions were implemented and compared in the experiments. The experimental results show that the proposed algorithm can effectively improve the inpainting precision and keep shape edges without increasing time complexity.

Key words: image inpainting, Curvature-Driven Diffusion (CCD) model, inpainting precision, time complexity