Towards Robust Underwater Image Enhancement

Jahroo Nabila Marvi, Laksmita Rahadianti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Underwater images often suffer from blurring and color distortion due to absorption and scattering in the water. Such effects are undesirable since they may hinder computer vision tasks. Many underwater image enhancement techniques have been explored to address this issue, each to varying degrees of success. The large variety of distortions in underwater images is difficult to handle by any singular method. This study observes four underwater image enhancement methods, i.e., Underwater Light Attenuation Prior (ULAP), statistical Background Light and Transmission Map estimation (BLTM), and Natural-based Underwater Image Color Enhancement (NUCE), and Global–Local Networks (GL-Net). These methods are evaluated on the Underwater Image Enhancement Benchmark (UIEB) dataset using quantitative metrics, e.g., SSIM, PSNR, and CIEDE2000 as the metrics. Additionally, a qualitative analysis of image quality attributes is also performed. The results show that GL-Net achieves the best enhancement result, but based on the qualitative assessment, this method still has room for improvement. A proper combination between the non-learning-based component and learning-based component should be investigated to further improve the robustness of the method.

Original languageEnglish
Title of host publicationSoft Computing in Data Science - 7th International Conference, SCDS 2023, Proceedings
EditorsMarina Yusoff, Murizah Kassim, Azlinah Mohamed, Tao Hai, Eisuke Kita
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages11
ISBN (Print)9789819904044
Publication statusPublished - 2023
Event7th International Conference on Soft Computing in Data Science, SCDS 2023 - Virtual, Online
Duration: 24 Jan 202325 Jan 2023

Publication series

NameCommunications in Computer and Information Science
Volume1771 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference7th International Conference on Soft Computing in Data Science, SCDS 2023
CityVirtual, Online


  • Deep learning
  • Image enhancement
  • Image restoration
  • Underwater images


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