Image Inpainting Based On Sparse Representation

As a key technology of image processing, image inpainting has been widely used in the research of biological vision systems, computer pattern recognition, medicine and other fields. At present, the research of image inpainting based on sparse representation is a new branch of this field in recent years. The image inpainting of sparse representation has very crucial practical significance and broad researching prospects. According to this, this paper mainly tries to do some research from the following aspects and concludes.1. The paper systematically studies the Morphological Component Analysis (MCA) sparse model, achieves the sparse decomposition of image based on the model of MCA and deals with the dirty image inpainting by combining the model of MCA &TV. Furthermore, the paper points out that the model of MCA could be combined with CDD to achieve the same result. The experiment turned out that the combination of MCA&CDD overcomes the shortcomings of MCA&TV in some extent and has a better performance in scratched image inpainting.2. The paper studies the VO model and the theory of Bregman iteration. Through bregman iterative, it solves VO model, thereby, achieve image sparse decomposition based on VO model. Combining the VO model, curvelet transform, local DCT transform with CDD model to achieve sparse image inpainting based on VO&CDD algorithm. Finally, the experiment shows that VO&CDD can achieve better sparse image inpainting.3. The paper introduces a new image decomposition model, named SAT, which combines the sparse representation with total variation. Using bregman iteration method solves this model and then applies to sparse decompose image and inpainting. The test shows that the SAT model can obtain almost perfect reconstructed image and has a better ability to inpainting the sparse image.In a word, this paper mainly studies the sparse decomposition model and the image inpainting based on sparse representation methods, and achieves the algorithms for the MCA&TV, MCA&CDD and VO&CDD inpainting and furthermore, achieves the image decomposition and sparse inpainting through the SAT model. Each of them carries out good performance.