Underwater Image Enhancement Algorithm Adapted to Different Turbidities Ranges

Z. Deng, Daxiong Ji, Lizhong Gu, M. Sun, Xin Yao
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Abstract

This paper proposed an image enhancement method that can adapt to changes in turbidity within a certain range. Establishing illumination intensity attenuation model based on light source carried by robot, we combine the absorption and scattering attenuation factors of the underwater medium with the turbidity of the water to obtain the defuzzified image. This method not only takes into account various complex attenuation media underwater, but also considers the changes in water quality in dynamic scenes. The proposed algorithm can be more adaptive to the motion of underwater robots. It can be seen from the comparative test analysis that the approach has strong robustness in a certain turbidity range.
适应不同浊度范围的水下图像增强算法
本文提出了一种能在一定范围内适应浊度变化的图像增强方法。建立基于机器人携带光源的光照强度衰减模型,将水下介质的吸收和散射衰减因子与水体浊度相结合,得到去模糊图像。该方法既考虑了水下各种复杂的衰减介质,又考虑了动态场景中水质的变化。该算法能更好地适应水下机器人的运动。从对比试验分析可以看出,该方法在一定浊度范围内具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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