Image Restoration Based on Pulse Coupled Neural Network

Image is the unity structure and texture, structure reflects to the contours and the boundaries between different regions in the image, and the texture is a reflection of the details within an area in the image, therefore the optimal restoration effect can not be achieved if structure or texture is considered separately during the process of image restoration. In order to solve the problems above, the corresponding solution proposed in this paper is as follows: first, the structural characteristics of the image to be repaired are obtained by using pulse coupled neural network; then both the textural features and the structural features are taken into consideration simultaneously when it comes to the priority of the image restoration as well as the calculation of the optimal sample block. It can be seen from the experimental results that the algorithm described herein can effectively improve the quality of image restoration.