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首页> 外文会议>International Conference on Robotics and Automation Sciences >An Underwater Image Enhancement Method for Simultaneous Localization and Mapping of Autonomous Underwater Vehicle
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An Underwater Image Enhancement Method for Simultaneous Localization and Mapping of Autonomous Underwater Vehicle

机译：一种水下图像增强方法，用于同时定位和自主水下车辆的映射

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Simultaneous localization and mapping (SLAM) has been treated as the key technology of the autonomous robots. This paper takes the application of visual SLAM in autonomous underwater vehicle (AUV) positioning as background. Unlike atmospheric imaging, underwater medium has issues with low contrast and color distortion. Here an underwater image enhancement method is brought forward to settle this problem. In this method, the image was converted from red-green-blue (RGB) color space into hue-saturation-value (HSV) color space, and the irradiation image was achieved after the guided filer was conducted on value component. The reflection image was obtained according to Retinex theory, and the image was converted back to RGB space. Finally, a gamma correction was applied to strength the image contrast. In the experiment, the images were exploited to perform SLAM. The results indicated that the enhanced images perform better than the original images in feature points extraction and visual SLAM.
机译：同时本地化和映射（SLAM）被视为自治机器人的关键技术。本文将视觉​​猛击在自动水下车辆（AUV）定位为背景中的应用。与大气成像不同，水下介质具有低对比度和颜色变形的问题。这里提出了一种水下图像增强方法来解决这个问题。在该方法中，图像从红色绿色（RGB）颜色空间转换为色调饱和值（HSV）颜色空间，并且在引导滤波器对值组分上进行照射图像来实现。根据Retinex理论获得反射图像，并且图像被转换回RGB空间。最后，施加伽马校正以强化图像对比度。在实验中，利用图像来执行SLAM。结果表明，增强型图像比特征点提取和视觉SLAM中的原始图像更好地执行。

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