Image Denoising via CNNs: An Adversarial Approach
传统的图像去噪算法大多需要知道噪声的先验知识,如高斯滤波通常对高斯噪声有效,而中值滤波通常对椒盐噪声有效等.文献提出了使用卷积神经网络的图像盲去噪模型,不需要先验信息,输入为单幅含噪图像,输出为清晰图像,模型结构图如下: 模型结构包括两部分: (1)多尺度特征提取: 使用多个不同大小的卷积核获取图像特征,以去除噪声的影响,并将所有的特征串联.每个卷积核层的output channels分别为:32
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