Criminisi-Based Sparse Representation for Image Inpainting
Gaolong Hu, Ling Xiong · 2017
Image inpainting is an important area in image processing, which has important application significance in the fields of cultural relic protection, inpainting of damaged old photographs and removal of redundant objects on images. Aiming at the drawbacks of the best matching block search and fill in Criminisi algorithm, and the superior performance of sparse representation in signal recovery, a Criminisi algorithm combined with sparse representation is proposed in this paper. In the proposed algorithm, the sparse representation inpainting method is used to replace the best matching patch search in Criminisi algorithm, and the marked areas to be inpainting are optimized and the priority of credibility is improved. The experimental results of image inpainting show that the proposed algorithm has strong adaptability and achieved good inpainting effect.