Enhancement algorithm for color images based on improved FC-MSPCNN
Yuan Kang, Jing Lian, Chenxi Guo, Li Zheng, Mingxuan Zhang · Journal of Physics Conference Series · 2021
Abstract Image enhancement has been a hot research topic in image processing in recent years, and Pulse-Coupled Neural Network (PCNN) based image processing has become one of the important channels for image processing. Recently, we have applied this network to image enhancement based on Fire-controlled Pulse-coupled NeuralNetwork (FC-MSPCNN) without changing its model structure by combining the adaptive parameter setting method to redefine the link coefficients β. On the one hand, and reprocessing the mapping matrix of the extracted three channels on the other hand. The experimental results of the improved FC-MSPCNN are proved to be more effective and robust compared with the traditional classical algorithm, both in terms of competent analysis and objective comparison.