Active Short-Long Exposure Deblurring

Abstract

Mobile phones can capture image bursts to produce high quality still photographs. The simplest form of a burst is two frame short-long (S-L) exposure. S-L exposure is particularly suitable in low light conditions where short exposure frames are sharp but noisy and dark, and long exposure frames are affected by motion blur but have better scene chromaticity and luminance. In this work, we take a step further and define active short-long exposure deblurring where the viewfinder frames before the burst are used to optimize the S-L exposure parameters. We introduce deep architectures and data generation for active S-L exposure deblurring. The approach is experimentally validated with realistic data and it shows clear improvements. For the most difficult scenes (worst 5%) the PSNR is improved by +1.39dB.