A Dive into SAM Prior in Image Restoration

Understand

The goal of image restoration (IR), a fundamental issue in computer vision, is to restore a high-quality (HQ) image from its degraded low-quality (LQ) observation.

• Multiple HQ solutions may correspond to an LQ input in this poorly posed problem, creating an ambiguous solution space.
• This motivates the investigation and incorporation of prior knowledge in order to effectively constrain the solution space and enhance the quality of the restored images.
• In spite of the pervasive use of hand-crafted and learned priors in IR, limited attention has been paid to the incorporation of knowledge from large-scale foundation models.