基于双层PCNN的多级灰度图像增强

Multilevel gray image contrast enhancement approach using double level PCNN

摘要: 在脉冲耦合神经网络(Plus Coupled Neural Network)模型基础上,提出了DLPCNN(Double Level PC-NN)模型.DLPCNN模型能有效地对多灰度级图像进行增强.该方法通过快速并行计算,分层处理、动态步长调整实现对多灰度级图像处理,与传统方法相比体现了较好的优势.

Abstract: It is presented DLPCNN(Double Level PCNN) model based on the PCNN(Pulse Coupled Neural Network).It is easy to solve the problem of multilevel gray image contrast enhancement.Compared with traditional method of multilevel image contrast enhancement,the proposed approach has better advantages in parallel calculation.Meanwhile,it is maked use of the DLPCNN by computing and modifying step to adapt dealing with multilevel image contrast enhancement.