Motion deblurring using spatiotemporal phase aperture coding

Shay Elmalem, Raja Giryes, Emanuel Marom

Research output: Contribution to journalArticlepeer-review

Abstract

Motion-related image blur is a known issue in photography. In practice, it limits the exposure time while capturing moving objects; thus, achieving proper exposure is difficult. Extensive research has been carried out to compensate for it, to allow increased light throughput without motion artifacts. In this work, a joint optical-digital processing method for motion deblurring is proposed and demonstrated. Using dynamic phase coding in the lens aperture during the image acquisition, the motion trajectory is encoded in an intermediate optical image. This coding embeds cues for both the motion direction and extent by coloring the spatial blur of each object. These color cues serve as guidance for a digital deblurring process, implemented using a convolutional neural network (CNN) trained to utilize such coding for image restoration. Particularly, unlike previous optical coding solutions, our strategy encodes cues with no limitation on the motion direction, and without sacrificing light efficiency. We demonstrate the advantage of the proposed approach over blind deblurring methods with no optical coding, as well as over other solutions that use coded acquisition, in both simulation and real-world experiments.

Original languageEnglish
Pages (from-to)1332-1340
Number of pages9
JournalOptica
Volume7
Issue number10
DOIs
StatePublished - Oct 2020

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