Research On The Models, Algorithms And Applications Of Digital Image Inpainting

Digital image inpainting is to fill in image information on a blank domain based on the image information available outsidd. It is an interpolation problem, which belongs to the field of restoration and it's also a branch of image processing. Applications of image inpainting range from restoration of photographs, films and paintings, to removal of occlusions, such as large unwanted regions, superimposed text, subtitles, stamps from images. In addition, it is more significant to restore the precious calligraphies and paintings in the museum with image inpainting technique. The widely-used applications of the image inpainting make this technique a hot research in the image processing techniques recently.Firstly,we summarize the recent work in this area ,discuss the particularity and methodology of inmage inpainting. Then, we are interested in the local inpainting methods, study several inpainting methods especially the Bertalmio- Sapiro-Caselles-B allester (BSCB) model and total variation (TV) model based on the Bayesian and variational principle with the comparision of results between two models.It is more effective for two models mentioned above to deal with the geometrical character of image and adaptive to non-texture. Therefore, in this thesis, we present a new image inpainting method based on the existing exemplar-based image inpainting idea. This method can obtain preferable results in human vision by rational Confidence and Data computing method.Finally, to overcome the disadvantage of those models mentioned above, we present two adaptive algorithms which combine image decomposition with local inpainting based on PDE and texture synthesis. Applying local inpainting and synthesis to non-texture and texture respectively gives satisfying results.