An in-situ image enhancement method for the detection of marine organisms by remotely operated vehicles

With the assistance of the visual system, remote operated vehicles (ROVs) can replace frogmen to achieve safer and more efficient capturing of marine organisms. However, the selective absorption and scattering of light lead to a decrease in the visual quality of underwater images, which hinders ROV operators from observing the operating environment. Unfortunately, most image enhancement methods only focus on image color correction rather than perceptual enhancement, which in turn prevents the object detector from quickly locating the target. Therefore, a visual-enhanced and detection-friendly underwater image enhancement method is needed. In this paper, an underwater image enhancement method called in-situ enhancement is proposed to improve the semantic information of the visual hierarchy based on current scene information in multiple stages. Mapping the underwater image to its dual space allows the enhancement equation to be applied to severely degraded underwater scenes. Moreover, it is also a detection-friendly method and has good generalization in both visual quality improvement and object detection. The experimental results show that in different underwater datasets, the in-situ enhancement effectively improves the visual quality of underwater images, and its enhanced results train different object detectors with high detection accuracy.