Due to the importance of underwater exploration in the development and utilization of deep-sea resources, underwater\nautonomous operation is more and more important to avoid the dangerous high-pressure deep-sea environment. For\nunderwater autonomous operation, the intelligent computer vision is the most important technology. In an underwater\nenvironment, weak illumination and low-quality image enhancement, as a preprocessing procedure, is necessary for underwater\nvision. In this paper, a combination of max-RGB method and shades of gray method is applied to achieve the enhancement of\nunderwater vision, and then a CNN (Convolutional Neutral Network) method for solving the weakly illuminated problem for\nunderwater images is proposed to train the mapping relationship to obtain the illumination map. After the image processing, a\ndeep CNN method is proposed to perform the underwater detection and classification, according to the characteristics of\nunderwater vision, two improved schemes are applied to modify the deep CNN structure. In the first scheme, a..................
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