Separating degradation information from scene content using orthogonal feature subspaces significantly improves all-in-one image restoration quality, achieving state-of-the-art results across multiple degradation types.
This paper tackles all-in-one image restoration—fixing multiple types of image damage (blur, noise, rain, etc.) in one model. The key problem is that existing methods mix degradation information with image content in a shared space, causing confusion.