Hybrid Inpainting Algorithm Based on Sparse Representation and Fast Inpainting Method

Image inpainting technique uses textural or structural information to repair or fill damaged potions of a picture. When dealing with a small area missing textural image, not only should guarantee the effectiveness of the algorithm, but the processing speed also need to be taken into account. In this paper, we propose a simply and effective inpainting method which combining fast inpainting method and source image dictionary based sparse representation inpainting method. The proposed method fully considers the complementary between the fast inpainting method and sparse representation inpainting approach. In this manner, our approach inpaints the small size textural missing image more effectively than the available inpainting method. The experimental results on practical images show that the proposed algorithm can achieve a plausible visual performance without the discontinuity boundary and blurring.