Criminisi-Based Sparse Representation for Image Inpainting

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.

[1]  Wei Hu,et al.  Image inpainting via sparse representation , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[2]  Tao Shao-jie An improved inpainting algorithm based on K-SVD dictionary , 2013 .

[3]  D. Donoho For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution , 2006 .

[4]  Michael Elad,et al.  K-SVD : DESIGN OF DICTIONARIES FOR SPARSE REPRESENTATION , 2005 .

[5]  Tony F. Chan,et al.  Mathematical Models for Local Nontexture Inpaintings , 2002, SIAM J. Appl. Math..

[6]  Patrick Pérez,et al.  Region filling and object removal by exemplar-based image inpainting , 2004, IEEE Transactions on Image Processing.

[7]  Rachid Deriche,et al.  Vector-valued image regularization with PDEs: a common framework for different applications , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Anupam,et al.  Fast and Enhanced Algorithm for Exemplar Based Image Inpainting , 2010, 2010 Fourth Pacific-Rim Symposium on Image and Video Technology.

[9]  Rajat Raina,et al.  Efficient sparse coding algorithms , 2006, NIPS.

[10]  Christine Guillemot,et al.  Image Inpainting : Overview and Recent Advances , 2014, IEEE Signal Processing Magazine.