Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

Understand

The aim of this paper is to propose a mechanism to efficiently and explicitly model image hierarchies in the global, regional, and local range for image restoration.

• To achieve that, we start by analyzing two important properties of natural images including cross-scale similarity and anisotropic image features.
• Inspired by that, we propose the anchored stripe self-attention which achieves a good balance between the space and time complexity of self-attention and the modelling capacity beyond the regional range.
• Then we propose a new network architecture dubbed GRL to explicitly model image hierarchies in the Global, Regional, and Local range via anchored stripe self-attention, window self-attention, and channel attention enhanced convolution.