Image Blind Denoising with Generative Adversarial Network Based Noise Modeling

• Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 3155 - 3164
• Main Authors: Chen, Jingwen, Chen, Jiawei, Chao, Hongyang, Yang, Ming
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Adaptation models; Gallium nitride; Generative adversarial networks; Noise measurement; Noise reduction; Training; Training data

In this paper, we consider a typical image blind denoising problem, which is to remove unknown noise from noisy images. As we all know, discriminative learning based methods, such as DnCNN, can achieve state-of-the-art denoising results, but they are not applicable to this problem due to the lack of...