摘要
针对现有的去噪算法,只能去除某一或两种特定的噪声,提出了基于卷积神经网络的图像混合噪声的去除算法.采用9层卷积网络,分别经过特征提取、维度收缩、非线性映射、维度放大和图像重构对含噪图像进行训练最终得到去噪模型.实验结果表明,算法生成的网络模型适用于含不同类型、不同程度的含噪图像的去噪,且在主观视觉效果和客观指标上均有很好的结果.
Aiming at the drawbacks of the denoised algrithms, that can only removal one or two specifickind of noise and are invalid for others, we combine some excellent neural network model and proposed the image mixed noise removal algorithm based on convolutional neural network. 9 convolution layers are adopted, and noise images are trained through feature extraction, shrinking,non-liner mapping,expanding and reconstruction. Experimental results show that the algorithm achieves better denoised results and is suitable for different kinds of mixed noise images. The subjective visual effect and objective evaluation indices are improved obviously.
出处
《微电子学与计算机》
CSCD
北大核心
2017年第12期11-15,共5页
Microelectronics & Computer
基金
国家自然科学基金(61471272)
湖北省自然科学基金(2016CFB499)
关键词
图像去噪
混合噪声
卷积神经网络
image denoise
mixed noise
convolutional neural network
