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Color restoration in turbid medium

Published: 18 December 2016 Publication History

Abstract

Light scattering and color distortions are two major issues with underwater imaging. Scattering occurs due to turbidity of the medium and color distortions are caused by differential attenuation of wavelengths as a function of depth. As a result, underwater images taken in a turbid medium have low contrast, color cast, and color loss. The main objective of this work is color restoration of underwater images i.e, produce its equivalent image as seen outside of the water surface. As a first step, we account for low contrast by employing dark channel prior based dehazing. These images are then color corrected by learning a mapping function between a pair of color chart images, one taken inside water and another taken outside. The mapping thus learned is with respect to a reference distance from the water surface. We also propose a color modulation scheme that is applied prior to color mapping to accommodate the same mapping function for different depths as well. Color restoration results are given on several images to validate the efficacy of the proposed methodology.

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Cited By

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  • (2021)Visibility improvement of underwater turbid image using hybrid restoration network with weighted filterMultidimensional Systems and Signal Processing10.1007/s11045-021-00795-833:2(459-484)Online publication date: 15-Nov-2021

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cover image ACM Other conferences
ICVGIP '16: Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing
December 2016
743 pages
ISBN:9781450347532
DOI:10.1145/3009977
© 2016 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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  • Google Inc.
  • QI: Qualcomm Inc.
  • Tata Consultancy Services
  • NVIDIA
  • MathWorks: The MathWorks, Inc.
  • Microsoft Research: Microsoft Research

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 December 2016

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Author Tags

  1. boosting
  2. color mapping
  3. color modulation
  4. dehazing
  5. white balancing

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ICVGIP '16
Sponsor:
  • QI
  • MathWorks
  • Microsoft Research

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ICVGIP '16 Paper Acceptance Rate 95 of 286 submissions, 33%;
Overall Acceptance Rate 95 of 286 submissions, 33%

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Cited By

View all
  • (2021)Visibility improvement of underwater turbid image using hybrid restoration network with weighted filterMultidimensional Systems and Signal Processing10.1007/s11045-021-00795-833:2(459-484)Online publication date: 15-Nov-2021

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