Real-World Underwater Enhancement: Challenges, Benchmarks, and Solutions Under Natural Light

Underwater image enhancement is such an important low-level vision task with many applications that numerous algorithms have been proposed in recent years. These algorithms developed upon various assumptions demonstrate successes from various aspects using different data sets and different metrics. In this work, we setup an undersea image capturing system, and construct a large-scale Real-world Underwater Image Enhancement (RUIE) data set divided into three subsets. The three subsets target at three challenging aspects for enhancement, i.e., image visibility quality, color casts, and higher-level detection/classification, respectively. We conduct extensive and systematic experiments on RUIE to evaluate the…

• NN
  National Natural Science Foundation of China

  Awards: 61733002, 61572096, 61672125, 61922019
• LR
  Liaoning Revitalization Talents Program

  Award: XLYC1807088
• FR
  Fundamental Research Funds for the Central Universities

  Award: DUT19TD19