Infrared Image Mosaic Based on Pulse Coupled Neural Network

Abstract

According to the infrared image noise interference serious and low signal to noise ratio characteristics, an image mosaic algorithm based on pulse coupled neural network is presented in this paper. The algorithm uses the PCNN imitation of biological vision to extract edge information, adopts the Hausdorff distance as the registration similarity measure, afterwards, computes the optimal registration parameters, simultaneously, uses the weighted average fusion method to achieve image mosaic. The experimental results show that the algorithm can achieve precise image mosaic and have better robustness to noise.