摘要
针对滤波去噪对边缘造成的弱化、部分采集图像不清晰以及对比度低的问题,在充分分析模型的动力学性质的基础上,提出一种基于六维前馈神经网络模型的图像增强算法。试验表明:基于六维前馈神经网络模型的图像增强算法可以更好地达到图像增强效果。与其它几种增强算法相比,增强效果清晰,且算法更优。
Aiming at the problems of weakening the edges caused by filtering denoising,partially indistinct images and lowcontrast,an image enhancement algorithm based on the six dimension feedforward neural network model was proposed on the basis of fully analyzing the dynamic properties of the model. The experiment showed that the image enhancement algorithm based on the six dimensional feedforward neural network model could better achieve a very good enhancement effect. Compared with other enhancement algorithms,the enhancement effect was clearer and the algorithm was better.
作者
张宪红
张春蕊
ZHANG Xianhong;ZHANG Chunrui(College of Computer Science and Technology,Heilongjiang Institue of Technogly,Harbin 150001,Heilongjiang,China;Department of Mathematics,Northeast Forestry University,Harbin 150001,Heilongjiang,China)
出处
《山东大学学报（工学版）》
CAS
北大核心
2018年第4期10-19,共10页
Journal of Shandong University（Engineering Science）
基金
黑龙江省哲学社会科学研究规划资助项目(16EDD05)
黑龙江工程学院博士科研启动基金资助项目(2017BJ15)
关键词
图像处理
图像增强
神经网络
六维前馈神经网络模型
动力系统
image processing
image enhancement
neural network
six dimensional feed-forward neural network model
dynamic system
