A New Approach of Image Inpainting Based on PSO Algorithm

In this paper, an efficient approach is developed to incorporate the exemplar-based image of inpainting method and the minimum error boundary of cut technique, that is proposed to improve the image inpainting in a more nature quality with high performance. The approach is based on the particle swarm optimization. Several advantages are addressed as follow. First, the image inpainting in texture with the linear structure is exploited to reasonably inpaint the damaged image in a high priority. Due to set the first priority to inpaint in the linear structure, such a method guarantees the integrality of the linear structure. In addition, the minimum error boundary of cut technique can effectively decrease the unnatural phenomena through inpainting the gap of damaged image. Owing to the damaged one will be dawdling extraordinarily if searching the similar block while inpainting. In this case, the method is proposed by joined the particle swarm optimization algorithm, and the outcome indeed improves the efficiency of image inpainting.