CurvPnP: Plug-and-play blind image restoration with deep curvature denoiser

发布时间：2022-11-30 作者：浏览次数：

Speaker:	段玉萍	DateTime:	2022年12月6日（星期二）上午11：00--12：00
Brief Introduction to Speaker: 段玉萍，教授，天津大学		Place:	腾讯会议（892873849）
Abstract:Due to the development of deep learning-based denoisers, the plug-and-play strategy has achieved great success in image restoration problems. However, existing plug-and-play image restoration methods are designed for non-blind Gaussian denoising, the performance of which visibly deteriorate for unknown noises. To push the limits of plug-and-play image restoration, we propose a novel framework with blind Gaussian prior, which can deal with more complicated image restoration problems in the real world. The experimental results on image denoising, deblurring and single-image super-resolution are provided to demonstrate the advantages of our deep curvature denoiser and the resulting plug-and-play blind image restoration method over the state-of-the-art model-based and learning-based methods. Our model is shown to be able to recover the fine image details and tiny structures even when the noise level is unknown for different image restoration tasks.