INFRARED IMAGE MULTI-THRESHOLD SEGMENTATION ALGORITHM BASED ON IMPROVED PULSE COUPLED NEURAL NETWORKS
基于改进的脉冲耦合神经网络的红外目标分割方法

By considering the features of targets in infrared images, a new image segmentation algorithm based on the pulse coupled neural network (PCNN) and histogram method was presented. The proposed algorithm entirely abandons the mechanism of the time exponential decaying function and uses the results of the gray level histogram analysis as the interior thresholds of PCNN. Meanwhile,it reserves the advantage of bridging small spatial gaps and minor intensity variations.Experiment results demonstrate that the proposed algorithm can get more complete region and edge information of infrared images. It is also of much lower complexity and of higher speed than the original one.