There is no more complicated, advantaged and powerful device than themammalian primate cortical visual system for image processing in nature.The pulse-coupled neural network (PCNN) is inspired from the investigationof pulse synchronization within the mammalian visual cortex, and has beenwidely applied to image processing and pattern recognition.
Visual cortex is the passage for brain to acquire information from eyesand a part of brain central nervous system. Several biological models basedon visual cortex were proposed through investigation of cat cortex and hadbeen applied to image processing.
The PCNN emulates the mammalian visual cortex, which is supposed tobe one of the most efficient image processing methods. The output of thePCNN is a series of pulse images which represent the fundamental featuresof original stimulus, such as edge, texture, and segment. Neurons receiveinputs from other neurons through synapses and are fired synchronously incertain regions, that is why the PCNN can be applied to image segmentation,smoothing, and coding. Another important feature of the PCNN is that thepulse images are able to be characterized to a unique invariant signature forthe image retrieval.
This book analyzes the PCNN in detail and presents some special appli-cations and corresponding results based on our own researches.
Contributions of the book have come from Hongjuan Zhang, RongchangZhao, Maojun Su, Dongmei Lin, Xiaojun Li, Guanzhu Xu, Xin Wang, Za-ifeng Zhang, Xiaowen Feng, Haibo Deng, Li Liu, Xiaozhe Xu, ChunliangQi, Chenghu Wu, Fei Shi, Zhibai Qian, Qing Liu, Min Yuan, Jiuwen Zhang,Yingjie Liu, Xiaolei Chen, and our graduate students at Circuit and SystemResearch Institute of Lanzhou University.