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Coded exposure photography: motion deblurring using fluttered shutter

Authors:

Jack TumblinAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 25, Issue 3

Pages 795 - 804

https://doi.org/10.1145/1141911.1141957

Published: 01 July 2006 Publication History

Abstract

In a conventional single-exposure photograph, moving objects or moving cameras cause motion blur. The exposure time defines a temporal box filter that smears the moving object across the image by convolution. This box filter destroys important high-frequency spatial details so that deblurring via deconvolution becomes an ill-posed problem.Rather than leaving the shutter open for the entire exposure duration, we "flutter" the camera's shutter open and closed during the chosen exposure time with a binary pseudo-random sequence. The flutter changes the box filter to a broad-band filter that preserves high-frequency spatial details in the blurred image and the corresponding deconvolution becomes a well-posed problem. We demonstrate that manually-specified point spread functions are sufficient for several challenging cases of motion-blur removal including extremely large motions, textured backgrounds and partial occluders.

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Cited By

Wang PKurihara TYu J(2025)CorNet: Enhancing Motion Deblurring in Challenging Scenarios Using Correlation Image SensorIEEE Access10.1109/ACCESS.2025.354359913(33834-33848)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3543599
Liu JFeng YWang YLiu JZhou FXiang WZhang YYang HCai CLiu FShao X(2024)Future-proof imaging: computational imagingAdvanced Imaging10.3788/AI.2024.200031:1(012001)Online publication date: 2024
https://doi.org/10.3788/AI.2024.20003
Cohen KMendlovic DRaviv D(2024)Temporal Super-Resolution Using a Multi-Channel Illumination SourceSensors10.3390/s2403085724:3(857)Online publication date: 28-Jan-2024
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Index Terms

Coded exposure photography: motion deblurring using fluttered shutter
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        Motion capture
  2. Computer graphics
    1. Animation
      1. Motion capture
      2. Motion processing
    2. Shape modeling
2. Theory of computation
  1. Randomness, geometry and discrete structures

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 25, Issue 3

July 2006

742 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1141911

Issue’s Table of Contents

Copyright © 2006 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 July 2006

Published in TOG Volume 25, Issue 3

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Cited By

Wang PKurihara TYu J(2025)CorNet: Enhancing Motion Deblurring in Challenging Scenarios Using Correlation Image SensorIEEE Access10.1109/ACCESS.2025.354359913(33834-33848)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3543599
Liu JFeng YWang YLiu JZhou FXiang WZhang YYang HCai CLiu FShao X(2024)Future-proof imaging: computational imagingAdvanced Imaging10.3788/AI.2024.200031:1(012001)Online publication date: 2024
https://doi.org/10.3788/AI.2024.20003
Cohen KMendlovic DRaviv D(2024)Temporal Super-Resolution Using a Multi-Channel Illumination SourceSensors10.3390/s2403085724:3(857)Online publication date: 28-Jan-2024
https://doi.org/10.3390/s24030857
Mizuno RTakahashi KYoshida MTsutake CFujii TNagahara H(2024)[Paper] Compressive Acquisition of Light Field Video Using Aperture-Exposure-Coded CameraITE Transactions on Media Technology and Applications10.3169/mta.12.2212:1(22-35)Online publication date: 2024
https://doi.org/10.3169/mta.12.22
Kohtani AMiyafuji SUragaki KKatsuyama HKoike H(2024)MOSion: Gaze Guidance with Motion-triggered Visual Cues by Mosaic PatternsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642577(1-11)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642577
Zhang xZhang LLi Y(2024)Laser active imaging deblurring technique based on random codingSixth Conference on Frontiers in Optical Imaging and Technology: Novel Technologies in Optical Systems10.1117/12.3015906(25)Online publication date: 30-Apr-2024
https://doi.org/10.1117/12.3015906
Ma YJiang JWang GLi JWang Z(2024)Dynamic Star Positioning Accuracy Improving Method Using Coded Exposure for Star SensorIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2024.338129673(1-12)Online publication date: 2024
https://doi.org/10.1109/TIM.2024.3381296
Yu TWang SChen WYu FLeung VTian Z(2024)Self-Supervised Adaptive Illumination Estimation for Low-Light Image EnhancementIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2024.33590518:2(1882-1893)Online publication date: Apr-2024
https://doi.org/10.1109/TETCI.2024.3359051
Baldwin RAsari VHirakawa K(2024)Sign-Coded Exposure Sensing for Noise-Robust High-Speed ImagingIEEE Transactions on Computational Imaging10.1109/TCI.2024.335991410(329-342)Online publication date: 2024
https://doi.org/10.1109/TCI.2024.3359914
Shahandashti PLópez PBrea VGarcía-Lesta DConde M(2024)Simultaneous Multifrequency Demodulation for Single-Shot Multiple-Path ToF ImagingIEEE Transactions on Computational Imaging10.1109/TCI.2023.334875810(54-68)Online publication date: 2024
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