Color Image Inpainting By an Improved Criminisi Algorithm
Yuting He, Xianghong Tang · ITM Web of Conferences · 2017
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.