Underwater Object Detection Enhancement via Channel Stabilization

The complex marine environment exacerbates the challenges of object detection manifold. With the advent of the modern era, marine trash presents a danger to the aquatic ecosystem, and it has always been challenging to address this issue with a complete grip. Therefore, there is a significant need to precisely detect marine deposits and locate them accurately in challenging aquatic surroundings. To ensure the safety of the marine environment caused by waste, the deployment of underwater object detection is a crucial tool to mitigate the harm of such waste. Our work explains the image enhancement strategies used and experiments exploring the best detection obtained after applying these methods. Specifically, we evaluate Detectron 2's backbone performance using different base models and configurations for the underwater detection task. We first propose a novel channel stabilization technique on top of a simplified image enhancement model to help reduce haze and color cast in training images. The proposed procedure shows improved results on multi-scaled objects present in the data set. Following image processing, we investigate various backbones in Detectron2 to provide the best detection accuracy for these images. In addition, we use a sharpening filter with augmentation techniques. This highlights the profile of the object, which helps us easily recognize it. We demonstrate our results by verifying them on the TrashCan Data set, both instance and material versions. We then explore the best-performing backbone method for this setting. We apply our channel stabilization and augmentation methods to the best-performing technique. We also compare our detection results from Detectron2 using the best backbones with those from Deformable Transformer. The detection result for small-sized objects in the instance-version of TrashCan 1.0 gives us a 9.53% absolute increase in average precision, while for the bounding box, we get an absolute gain of 7% compared to the baseline. The code will be available on Code: https://github.com/aliman80/Underwater-Object-Detection-via-Channel-Stablization