article

Video enhancement using per-pixel virtual exposures

Authors:

Eric P. Bennett,

Leonard McMillanAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 24, Issue 3

Pages 845 - 852

https://doi.org/10.1145/1073204.1073272

Published: 01 July 2005 Publication History

Abstract

We enhance underexposed, low dynamic range videos by adaptively and independently varying the exposure at each photoreceptor in a post-process. This virtual exposure is a dynamic function of both the spatial neighborhood and temporal history at each pixel. Temporal integration enables us to expand the image's dynamic range while simultaneously reducing noise. Our non-linear exposure variation and denoising filters smoothly transition from temporal to spatial for moving scene elements. Our virtual exposure framework also supports temporally coherent per frame tone mapping. Our system outputs restored video sequences with significantly reduced noise, increased exposure time of dark pixels, intact motion, and improved details.

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Cited By

Zhou RLi PZhang MLin QWang YBian XZhou FWang R(2024)A Low-Light Image Enhancement Algorithm Incorporating Cross-Mixed Attention and Receptive Field Expansion MechanismIEEE Access10.1109/ACCESS.2024.338151412(45773-45784)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3381514
Xie CLiu JWang YDong SXu QLiu J(2024)Preprocessing method for digital X-Ray weld imagesJournal of Physics: Conference Series10.1088/1742-6596/2770/1/0120162770:1(012016)Online publication date: 1-May-2024
https://doi.org/10.1088/1742-6596/2770/1/012016
Qian WDong SChen LRen Q(2024)Image enhancement method for low-light pipeline weld X-ray radiographs based on weakly supervised deep learningNDT & E International10.1016/j.ndteint.2024.103049143(103049)Online publication date: Apr-2024
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Index Terms

Video enhancement using per-pixel virtual exposures
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation
    2. Rendering

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 24, Issue 3

July 2005

826 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1073204

Issue’s Table of Contents

Copyright © 2005 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 2005

Published in TOG Volume 24, Issue 3

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Cited By

Zhou RLi PZhang MLin QWang YBian XZhou FWang R(2024)A Low-Light Image Enhancement Algorithm Incorporating Cross-Mixed Attention and Receptive Field Expansion MechanismIEEE Access10.1109/ACCESS.2024.338151412(45773-45784)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3381514
Xie CLiu JWang YDong SXu QLiu J(2024)Preprocessing method for digital X-Ray weld imagesJournal of Physics: Conference Series10.1088/1742-6596/2770/1/0120162770:1(012016)Online publication date: 1-May-2024
https://doi.org/10.1088/1742-6596/2770/1/012016
Qian WDong SChen LRen Q(2024)Image enhancement method for low-light pipeline weld X-ray radiographs based on weakly supervised deep learningNDT & E International10.1016/j.ndteint.2024.103049143(103049)Online publication date: Apr-2024
https://doi.org/10.1016/j.ndteint.2024.103049
Gao X(2023)Image enhancement method based on multi algorithm fusionHighlights in Science, Engineering and Technology10.54097/hset.v60i.1033860(52-62)Online publication date: 25-Jul-2023
https://doi.org/10.54097/hset.v60i.10338
Lv XZhang SWang CZhang WYao HHuang Q(2023)Unsupervised Low-Light Video Enhancement With Spatial-Temporal Co-Attention TransformerIEEE Transactions on Image Processing10.1109/TIP.2023.330133232(4701-4715)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIP.2023.3301332
Li ZShao YZhang FZhang JWang YSang N(2023)Difficulty-Aware Dynamic Network for Lightweight Exposure CorrectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.334050634:6(5033-5048)Online publication date: 7-Dec-2023
https://dl.acm.org/doi/10.1109/TCSVT.2023.3340506
Liu SLiu S(2023)Low-Exposure Image and Video EnhancementImage and Video Color Editing10.1007/978-3-031-26030-8_7(65-75)Online publication date: 21-Mar-2023
https://doi.org/10.1007/978-3-031-26030-8_7
Liu WZhao PSong XZhang B(2022)A Survey of Low-light Image EnhancementFrontiers in Computing and Intelligent Systems10.54097/fcis.v1i3.22421:3(88-92)Online publication date: 30-Oct-2022
https://doi.org/10.54097/fcis.v1i3.2242
Lohani DCrispim-Junior CBarthélemy QBertrand SRobinault LTougne Rodet L(2022)Perimeter Intrusion Detection by Video Surveillance: A SurveySensors10.3390/s2209360122:9(3601)Online publication date: 9-May-2022
https://doi.org/10.3390/s22093601
Akhtar NSaddique MAsghar KBajwa UHussain MHabib Z(2022)Digital Video Tampering Detection and Localization: Review, Representations, Challenges and AlgorithmMathematics10.3390/math1002016810:2(168)Online publication date: 6-Jan-2022
https://doi.org/10.3390/math10020168
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