Underwater Target Detection Based on Deep Neural Network and Image Enhancement

Abstract

Underwater target detection tasks refer to the detection of targets contained in underwater images. Unlike traditional target detection tasks, for underwater targets, due to factors such as illumination, camera shake, complex background interference, and diversification of target types, the effect of target detection will be affected. In this paper, we propose a target detection algorithm based on image enhancement and deep network. The algorithm first enhances the image data to obtain a better contrast, and then uses a deep learning algorithm to separate the target and the background to improve the detection performance of the target. Experimental results show that the algorithm can achieve better detection performance.