A New Method of PCNN's Parameter's Optimization

Recent research in neuroscience has proposed a new artificial neural networks model,the pulse coupled neural networks,PCNN.Several PCNN structures for image processing have been proposed depending on the model's potential.In the research of the theories and the applications of PCNN,it isn't a trivial task to define the relative parameters properly,and people usually get the values by experience with many experiments.As a contribution to this research field,this paper presents a new method for image processing based on the image histogram of gray-level and amount of information.The histogram is used as a new tool to describe the image features and furthermore to define the decay time constant of PCNN.With this new algorithm,we can get perfect segmentation result with the fewest iteration times only in one computation period of PCNN,and also can resolve the problem in image segmentation that it is liable to loss some object while many objects exist.Experiments show that the new algorithm has good performance in image processing.