In this paper, we aim to solve complex real-world image restoration situations, in which, one image may have a variety of unknown degradations. To this end, we propose an all-in-one image restoration framework with latent diffusion (AutoDIR), which can automatically detect and address multiple unknown degradations. Our framework first utilizes a Blind Image Quality Assessment Module (BIQA) to automatically detect and identify the unknown dominant image degradation type of the image. Then, an All-in-One Image Editing (AIR) Module handles multiple kinds of degradation image restoration with the guidance of BIQA. Finally, a Structure Correction Module (SCM) is proposed to recover the image details distorted by AIR. Our comprehensive evaluation demonstrates that AutoDIR outperforms state-of-the-art approaches by achieving superior restoration results while supporting a wider range of tasks. Notably, AutoDIR is also the first method to automatically handle real-scenario images with multiple unknown degradations.

本文提出了一种全方位图像修复框架，通过自动检测和处理多种未知的图像退化，实现了对复杂实际图像修复问题的解决。该框架利用盲图像质量评估模块进行未知主要图像退化类型的自动检测和识别，然后使用全方位图像编辑模块进行多种退化图像修复，并通过结构校正模块恢复AIR导致的图像细节失真。综合评估表明，AutoDIR在支持更多任务的同时，通过取得优越的修复结果超越了现有方法。值得注意的是，AutoDIR还是首个能够自动处理多种未知图像退化的方法。

AutoDIR：自动全能图像修复与潜在扩散