Image Inpainting Based On Priori Constraints And Contour Feature

When the damaged area of the image contains both rich texture information and geometric structure information,if the texture is incorrectly extended due to the texture information and geometric structure information of the damaged image can't be properly distinguished by using exemplar based algorithm.The repair result will be structurally fractured.To solve the problems,two improved methods of PatchMatch algorithm and Criminisi algorithm are proposed,in this thesis,that are based on the prior knowledge and contour features of the repaired image.Firstly,in order to slove the mis-matching problems of the PatchMatch algorithm that caused by using random methods to initialize image offset mapping and emploing approximate nearest-neighbor propagation modes.The image prior information such as texture information and geometric structure information is introduced into the PatchMatch algorithm for initializing of the image offset mapping.The random initialization method of the PatchMatch algorithm is improved by using the image prior knowledge constraint.Furthermore,in order to improve the matching accuracy of the PatchMatch algorithm,a similarity measure formula that can distinguish image geometry information and texture information is used to measure the similarity of two image patches.To reduce the computational complexity of the proposed algorithm,the statistical characteristics of similar patches is introduced to cut the sample tags that are used for repairing demange image.At last,gradient factor is introduced into the smoothing term of the algorithm to improve the sensitivity of the algorithm to structural information.Secondly,for the purpose of solving the defect of the exemplar-based algorithm in the consistency of the image structure,an improved contour reconstruction algorithms is proposed for reconstructing the contour information of the damaged area based on the global selfsimilarity of image.The contour features of the image are used to guide the contour reconstruction of the damaged area in the proposed algorithm for improving the visual consistency of repaired results.The contour information is introduced to improve the priority of Criminisi algorithm for ensuring the propagation of structural information from the edge of the damaged area to the inside.For matching the sample patch,the matching accuracy of the algorithm can be improved by constraining the search range of the matching patch based on the contour information of the image.Finally,the simulation results show that the repaired effect of the proposed algorithm has a higher peak signal-to-noise ratio(PSNR)and structural similarity(SSIM)compared to other similar improved algorithms.Therefore,the visual connectivity requirements of human beings can be satisfied by adopting the proposed algorithm.