Restoration of Out-of-focus Lecture Video by Automatic Slide Matching

Restoring the fine detail in the slide area of a defocused lecture video is a challenging task. In this work, we propose to use clean images of slides available along with the defocused lecture video to help the restoration. Our proposed method uses local feature descriptors and multiple defocused slide decks to automatically identify the slide that is displayed in the defocused frame. We then use the matching slide as side information to estimate the parameters for deconvolution and bilateral filtering. Experimental results show that the proposed algorithm compares favorably to a computationally-intensive iterative deconvolution algorithm that does not employ any side information. In particular, it can recover small drawings and text that are severely blurred in a poorly focused lecture video