Frontiers in Marine Science (Sep 2023)

Low-illumination underwater image enhancement based on non-uniform illumination correction and adaptive artifact elimination

  • Yu Ning,
  • Yong-Ping Jin,
  • You-Duo Peng,
  • Jian Yan

DOI
https://doi.org/10.3389/fmars.2023.1249351
Journal volume & issue
Vol. 10

Abstract

Read online

High-quality underwater images are used to extract information for a variety of purposes, including habitat characterization, species monitoring, and behavioral analysis. However, due to the limitation of non-uniform illumination environment and equipment, these images often have the problem of local over- or underexposure due to non-uniform illumination. Conventional methods cannot fully correct for this, and the dark area artifacts generated in the process of enhancing a low-light image cannot be readily fixed. Therefore, we describe a low-illumination underwater image enhancement method based on non-uniform illumination correction and adaptive artifact elimination. First, to eliminate the influence of non-uniform illumination on underwater images, an illumination equalization algorithm based on non-linear guided filtering corrects the non-uniform bright and dark regions of underwater images, and the dark channel prior algorithm and contrast-limited adaptive histogram equalization algorithm are introduced to prevent excessive enhancement of images and generation of dark regions. Then, in order to adaptively eliminate the dark area artifacts generated during the enhancement process, an adaptive multi-scale Retinex color fidelity algorithm with color restore is proposed to improve the color of the image and adaptively eliminate the dark area artifacts of the image. Then, the gray world white balance algorithm is used to adjust the color distortion caused by the attenuation of light. Finally, a multi-scale Retinex model parameter estimation algorithm is proposed to obtain the illumination component and reflection component of the image, and then, the enhanced image is obtained according to the Retinex model. The results show that the proposed method is superior to other algorithms regarding contrast, color restoration, and comprehensive effect, and improves low-illumination image enhancement technology.

Keywords