Official implementation.
Xingyu Jiang, Xiuhui Zhang, Ning Gao, Yue Deng *
School of Astronautics, Beihang University, Beijing, China
- Oct 17, 2024: The train code is now open and our paper is available here!
- Jul 25, 2024: Paper accepted at ECCV 2024.
Abstract: Natural images can suffer from various degradation phenomena caused by adverse atmospheric conditions or unique degradation mechanism. Such diversity makes it challenging to design a universal framework for kinds of restoration tasks. Instead of exploring the commonality across different degradation phenomena, existing image restoration methods focus on the modification of network architecture under limited restoration priors. In this work, we first review various degradation phenomena from a frequency perspective as prior. Based on this, we propose an efficient image restoration framework, dubbed SFHformer, which incorporates the Fast Fourier Transform mechanism into Transformer architecture. Specifically, we design a dual domain hybrid structure for multi-scale receptive fields modeling, in which the spatial domain and the frequency domain focuses on local modeling and global modeling, respectively. Moreover, we design unique positional coding and frequency dynamic convolution for each frequency component to extract rich frequency-domain features. Extensive experiments on thirty-one restoration datasets for a range of ten restoration tasks such as deraining, dehazing, deblurring, desnowing, denoising, super-resolution and underwater/low-light enhancement, demonstrate that our SFHformer surpasses the state-of-the-art approaches and achieves a favorable trade-off between performance, parameter size and computational cost.
Experiments are performed for different image restoration tasks including, image dehazing, image deraining, image desnowing, image denoising, image super-resolution, single-image motion deblurring, defocus deblurring, image raindrop removal, low-light image enhancement and underwater image enhancement.
Image Dehazing (click to expand)
Image Deraining (click to expand)
Image Desnowing (click to expand)
Image Super-resolution (click to expand)
Image Raindrop Removal (click to expand)
Single-Image Motion Deblurring (click to expand)
Defocus Deblurring (click to expand)
Image Denoising (click to expand)
Underwater Image Enhancement (click to expand)
Low-light Image Enhancement (click to expand)
