Photosequencing of Motion Blur using Short and Long Exposures

TL;DR

This paper introduces a method to generate sharp image sequences from a single motion blurred photo by capturing additional short exposure images and applying a recursive blur decomposition, improving motion resolution.

Contribution

It proposes a novel blur decomposition strategy using short and long exposures to recover sharp image sequences from motion blurred images.

Findings

Better resolution of fast and fine motions compared to prior methods

Effective use of short exposure images to aid in deblurring

Validated on diverse scenes with interesting motions

Abstract

Photosequencing aims to transform a motion blurred image to a sequence of sharp images. This problem is challenging due to the inherent ambiguities in temporal ordering as well as the recovery of lost spatial textures due to blur. Adopting a computational photography approach, we propose to capture two short exposure images, along with the original blurred long exposure image to aid in the aforementioned challenges. Post-capture, we recover the sharp photosequence using a novel blur decomposition strategy that recursively splits the long exposure image into smaller exposure intervals. We validate the approach by capturing a variety of scenes with interesting motions using machine vision cameras programmed to capture short and long exposure sequences. Our experimental results show that the proposed method resolves both fast and fine motions better than prior works.