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Dense scattering layer removal

Published: 19 November 2013 Publication History

Abstract

We propose a new model, together with advanced optimization, to separate a thick scattering media layer from a single natural image. It is able to handle challenging underwater scenes and images taken in fog and sandstorm, both of which are with significantly reduced visibility. Our method addresses the critical issue -- this is, originally unnoticeable impurities will be greatly magnified after removing the scattering media layer -- with transmission-aware optimization. We introduce non-local structure-aware regularization to properly constrain transmission estimation without introducing the halo artifacts. A selective-neighbor criterion is presented to convert the unconventional constrained optimization problem to an unconstrained one where the latter can be efficiently solved.

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Cited By

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  • (2023)Rank-One Prior: Real-Time Scene RecoveryIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.3226276(1-17)Online publication date: 2023
  • (2021)Rank-One Prior: Toward Real-Time Scene Recovery2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.01456(14797-14805)Online publication date: Jun-2021
  • (2020)Fast Visibility Restoration Using a Single Degradation Image in Scattering MediaIEEE Photonics Journal10.1109/JPHOT.2020.298827912:3(1-13)Online publication date: Jun-2020
  • Show More Cited By

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Published In

cover image ACM Conferences
SA '13: SIGGRAPH Asia 2013 Technical Briefs
November 2013
135 pages
ISBN:9781450326292
DOI:10.1145/2542355
  • Conference Chairs:
  • Baoquan Chen,
  • Andrei Sharf
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 November 2013

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Author Tags

  1. haze removal
  2. noise reduction

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  • Research-article

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SA '13
Sponsor:
SA '13: SIGGRAPH Asia 2013
November 19 - 22, 2013
Hong Kong, Hong Kong

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Overall Acceptance Rate 178 of 869 submissions, 20%

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Cited By

View all
  • (2023)Rank-One Prior: Real-Time Scene RecoveryIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.3226276(1-17)Online publication date: 2023
  • (2021)Rank-One Prior: Toward Real-Time Scene Recovery2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.01456(14797-14805)Online publication date: Jun-2021
  • (2020)Fast Visibility Restoration Using a Single Degradation Image in Scattering MediaIEEE Photonics Journal10.1109/JPHOT.2020.298827912:3(1-13)Online publication date: Jun-2020
  • (2019)Relative CNN-RNNIEEE Transactions on Image Processing10.1109/TIP.2018.285721928:1(45-55)Online publication date: 1-Jan-2019
  • (2019)Pseudo-polarimetric Method for Dense Haze RemovalIEEE Photonics Journal10.1109/JPHOT.2018.289077111:1(1-11)Online publication date: Feb-2019
  • (2019)Single Image Dehazing Using Non-local Total Generalized Variation2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA)10.1109/ICIEA.2019.8833710(19-24)Online publication date: Jun-2019
  • (2018)Single Image Dehazing Using Ranking Convolutional Neural NetworkIEEE Transactions on Multimedia10.1109/TMM.2017.277147220:6(1548-1560)Online publication date: Jun-2018
  • (2018)Automatic Building Rooftop Extraction From Aerial Images via Hierarchical RGB-D PriorsIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2018.285097256:12(7369-7387)Online publication date: Dec-2018
  • (2018)Near-Infrared Fusion via Color Regularization for Haze and Color Distortion RemovalsIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2017.274815028:11(3111-3126)Online publication date: 1-Nov-2018
  • (2018)Polarimetric image recovery method combining histogram stretching for underwater imagingScientific Reports10.1038/s41598-018-30566-88:1Online publication date: 20-Aug-2018
  • Show More Cited By

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