Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Enhancing Underwater Images through Deep Curve Estimation

깊은 곡선 추정을 이용한 수중 영상 개선

  • Muhammad Tariq Mahmood (Korea University of Technology and Education, School of Computer Science and Engineering) ;
  • Young Kyu Choi (Korea University of Technology and Education, School of Computer Science and Engineering)
  • Received : 2024.05.01
  • Accepted : 2024.06.21
  • Published : 2024.06.30
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Abstract

Underwater images are typically degraded due to color distortion, light absorption, scattering, and noise from artificial light sources. Restoration of these images is an essential task in many underwater applications. In this paper, we propose a two-phase deep learning-based method, Underwater Deep Curve Estimation (UWDCE), designed to effectively enhance the quality of underwater images. The first phase involves a white balancing and color correction technique to compensate for color imbalances. The second phase introduces a novel deep learning model, UWDCE, to learn the mapping between the color-corrected image and its best-fitting curve parameter maps. The model operates iteratively, applying light-enhancement curves to achieve better contrast and maintain pixel values within a normalized range. The results demonstrate the effectiveness of our method, producing higher-quality images compared to state-of-the-art methods.

Keywords

Acknowledgement

이 논문은 2023년도 한국기술교육대학교 교수 교육연구진흥과제 지원에 의하여 연구되었음.

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