Color Image Inpainting By an Improved Criminisi Algorithm

Abstract

Due to the incorrect filling order and the fixed size of patch, the traditional examplar-based image inpainting algorithm tends to cause the image structure fracture, texture error extension and so on. So in this paper, it proposes an improved Criminisi algorithm with adaptive adjustment with gradient variation to color image inpainting algorithm. Firstly, to overcome the discontinuity of the edge structure caused by the incorrect filling order, using curvature of isophotes to constraint the filling order. Secondly, in order to solve the lack of the step effect in rich texture region, it adaptively adjusts the sample patch size according to the variation of local gradient. Finally, the local search method is used to find the best matching patch. The experimental results show that the proposed algorithm's PSNR increased by 1-3dB and obtain better results in terms of different types of images.

A fast image inpainting algorithm based on an adaptive scanning strategy

“…Wang et al [35] introduced regularization items to avoid the loss of priority item, and adjusted the search strategy of matching patches, thus improving the robustness of the method. Wang et al [36] also proposed an image inpainting method based on structure tensor and adopted an improved matching patch similarity calculation method to improve the effectiveness of the algorithm.…”