Abstract
The visual system is one of the main equipment of unmanned surface vehicle (USV) autonomous navigation. Under the sea fog, atmospheric particles scattering leads to serious image degradation of the visual system. Because there is obvious sea-sky-line and the larger sky area in the image of offshore, so firstly, the image segmentation is done to get sky area, and through anglicizing sky area characteristics, the sky brightness is estimated, and then a simplified physical model of atmospheric scattering is built up, lastly image scene recovery is finished. Thinking about using this simple image defogging method to video image, foreground and background separation is done. Comparative research with several defogging methods onshore, results show that the proposed method can enhance the video image clarity of the USV visual system under sea fog very well. This research brought a good foundation to further improve the accuracy and precision of surface target identification and tracking algorithm.
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Ma, Z., Wen, J., Liang, X. (2013). Video Image Clarity Algorithm Research of USV Visual System under the Sea Fog. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_52
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DOI: https://doi.org/10.1007/978-3-642-38715-9_52
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