There are many tasks that require clear and easily recognizable images in the field of\nunderwater robotics and marine science, such as underwater target detection and identification of\nrobot navigation and obstacle avoidance. However, water turbidity makes the underwater image\nquality too low to recognize. This paper proposes the use of the dark channel prior model for\nunderwater environment recognition, in which underwater reflection models are used to obtain\nenhanced images. The proposed approach achieves very good performance and multi-scene\nrobustness by combining the dark channel prior model with the underwater diffuse model.\nThe experimental results are given to show the effectiveness of the dark channel prior model in\nunderwater scenarios.
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