Underwater image enhancement by Dehazing with minimum information loss and histogram distribution prior

Chongyi LI, Jichang GUO*, Runmin CONG, Yanwei PANG, Bo WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

566 Citations (Scopus)

Abstract

Images captured under water are usually degraded due to the effects of absorption and scattering. Degraded underwater images show some limitations when they are used for display and analysis. For example, underwater images with low contrast and color cast decrease the accuracy rate of underwater object detection and marine biology recognition. To overcome those limitations, a systematic underwater image enhancement method, which includes an underwater image dehazing algorithm and a contrast enhancement algorithm, is proposed. Built on a minimum information loss principle, an effective underwater image dehazing algorithm is proposed to restore the visibility, color, and natural appearance of underwater images. A simple yet effective contrast enhancement algorithm is proposed based on a kind of histogram distribution prior, which increases the contrast and brightness of underwater images. The proposed method can yield two versions of enhanced output. One version with relatively genuine color and natural appearance is suitable for display. The other version with high contrast and brightness can be used for extracting more valuable information and unveiling more details. Simulation experiment, qualitative and quantitative comparisons, as well as color accuracy and application tests are conducted to evaluate the performance of the proposed method. Extensive experiments demonstrate that the proposed method achieves better visual quality, more valuable information, and more accurate color restoration than several state-of-the-art methods, even for underwater images taken under several challenging scenes.

Original languageEnglish
Article number7574330
Pages (from-to)5664-5677
Number of pages14
JournalIEEE Transactions on Image Processing
Volume25
Issue number12
Early online date22 Dec 2016
DOIs
Publication statusPublished - Dec 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1992-2012 IEEE.

Keywords

  • contrast enhancement
  • scattering removal
  • underwater image dehazing
  • Underwater image enhancement

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