Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration

Mauricio Delbracio, Peyman Milanfar

Abstract: Inversion by Direct Iteration (InDI) is a new formulation for supervised image restoration that avoids the so-called “regression to the mean” effect and produces more realistic and detailed images than existing regression-based methods. It does this by gradually improving image quality in small steps, similar to generative denoising diffusion models.