Inpainting Model, Algorithm And Its Application

Inpainting is to fill in image information on a blank domain based upon the image information available outside, it is a interpolation problem. It has wide applications in restoring scratched old photos, disocclusions in vision analysis, text removal from images, and digital zoomings. Image inpainting is a new area of image restoration. Recently, it is regarded by many researchers in Image Processing area at home and abroad.First, we summarized the recent work in this area, discussed the particularity and methodology of Image Inpainting. then, we are interested in the local inpainting methods, studied several inpainting methods especially the Bertalmio-Sapiro-Caselles-Ballester (BSCB) modal and Curvature Driven Diffusions (CDD) modal based on PDE, and Tikhonov model and total variation (TV) modal based on the Bayesian and variational principles. These models are discussed for local non-texture images and not fit for textures, texture synthesize and and best neighborhood matching (BNM) modal shows them amazing effect in texture area.To overcome the disadvantage of those models mentioned above, the combination of image decomposition with image inpainting and texture synthesis become more popular. We studied two models, Shantanu Rane model and Vese-Osher model. Further experiments are to be carried out to obtain the best combination of image decomposition, image inpainting and texture synthesis.