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.

翻译：本文旨在解决复杂现实场景中图像可能同时存在多种未知退化的问题。为此，我们提出了一种基于潜在扩散的全能图像修复框架（AutoDIR），可自动检测并处理多种未知退化类型。该框架首先利用盲图像质量评估模块（BIQA）自动检测并识别图像中占主导地位的未知退化类型；其次，设计全能图像编辑模块（AIR），在BIQA引导下实现多种退化图像的联合修复；最后，提出结构校正模块（SCM）以恢复AIR模块导致的图像细节失真。综合评估表明，AutoDIR在支持更广泛任务的同时取得了优于现有方法的修复效果。值得注意的是，AutoDIR是首个能够自动处理含多种未知退化真实场景图像的方法。