A real image denoising algorithm based on convolutional neural network was proposed in order to solve the problem of image detail loss caused by artifacts generated by the original denoising algorithm,which consisted of a feature extraction module and a clean image generator.The feature extraction module was used to encode and extract features from the input noisy image;The expression ability of image features was enhanced,and the extracted image features were input into the clean image generator for learning image features,decoding,and then restoring the clean image.When recovering clean images,artifacts are reduced,image details can be better preserved,and high-quality clean images can be separated from noisy images.The test results on the SIDD and DND real noise datasets show that the PSNR values are 35.12,36.89 dB,and the SSIM values are 0.951,0.945,respectively.The proposed algorithm in this paper can effectively remove noise from real images,and the denoising results have advanced performance in both objective evaluation and subjective evaluation.
关键词
深度学习/卷积神经网络/图像去噪/真实噪声/注意力机制
Key words
Deep Learning/convolutional neural network/Image Denoising/real noise/attention mechanism
维普
万方数据