Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions

TL;DR

This paper introduces a comprehensive real-world underwater image dataset and systematically evaluates various enhancement algorithms, revealing their effectiveness and limitations, and exploring their impact on higher-level vision tasks like object detection.

Contribution

The work constructs a large-scale, multi-faceted underwater image dataset and provides a systematic evaluation of enhancement algorithms, including their effects on downstream tasks.

Findings

Algorithms improve visibility and color correction but have limitations.

Enhanced images can improve object detection performance.

New insights guide future underwater image enhancement research.

Abstract

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 effectiveness and limitations of various algorithms to enhance visibility and correct color casts on images with hierarchical categories of degradation. Moreover, underwater image enhancement in practice usually serves as a preprocessing step for mid-level and high-level vision tasks. We thus exploit the object detection performance on enhanced images as a brand new task-specific evaluation criterion. The findings from these evaluations not only confirm what is commonly believed, but also suggest promising solutions and new directions for visibility enhancement, color correction, and object detection on real-world underwater images.