真实场景中基于卷积神经网络的去噪算法

Denoising Algorithm Based on Convolutional Neural Network in Real Scene

针对真实场景中的噪声图像处理,根据更接近真实场景中的噪声模型,提出了一种基于卷积神经网络的去噪算法,该算法利用卷积神经网络中多个卷积层学习真实场景下噪声图像的数据特征,从而不断优化自身参数。仿真结果表明,本文所提基于卷积神经网络的去噪算法对真实场景中的噪声图像具有较好的去噪效果,去噪后的图像更加清晰,视觉效果较好,同时图像中的边缘细节得到了较好的保持。

For dealing with the noise image processing in the real scene,this paper proposes a denoising algorithm based on convolutional neural network according to the noise model which closer to the real scene.The algorithm uses multiple convolution layers in the convolutional neural network to learn the data characteristics of the noise image in the real scene,so as to continuously optimize its own parameters.The simulation results show that the denoising algorithm based on convolutional neural network has a good denoising effect on the noise image in real scene,the denoised image is clearer,the visual effect is better,and the edge details in the image are well preserved.