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Enhancement of Underwater Images in Low-to-High Turbidity Rivers

机译:从低到高浊度河流的水下图像增强

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The demand for efficient enhancement methods of underwater images of the rivers in the Amazon region is increasing. However, most of those in the region present moderate turbidity and low luminosity. This work aims to improve these images by non-linear filtering techniques, which promote the minimization of light interaction characteristics with the environment, loss of the contrast and colors. The proposed method is compared with two others techniques that requires a unique image as input. The results of the proposed method is promising, with better visual quality considering a wide range of experiments with simulation data and real outdoor scenes.
机译:对亚马逊地区河流水下图像的有效增强方法的需求正在增加。但是,该地区的大多数浊度中等,发光度低。这项工作旨在通过非线性滤波技术来改善这些图像,从而促进与环境的光交互特性,对比度和颜色损失的最小化。将提出的方法与需要唯一图像作为输入的其他两种技术进行了比较。所提出的方法的结果是有希望的,考虑到具有模拟数据和真实室外场景的大量实验,具有更好的视觉质量。

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