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Visibility enhancement for underwater visual SLAM based on underwater light scattering model

机译:基于水下光散射模型的水下视觉SLAM可视性增强

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This paper presents a real-time visibility enhancement algorithm for effective underwater visual simultaneous localization and mapping (SLAM). Unlike an aerial environment, an underwater environment contains larger particles and is dominated by a different image degradation model. Our method starts with a thorough understanding of underwater particle physics (e.g., forward, back, multiple scattering, blur and noise). Targeting underwater image enhancement in a real-world application, we include an artificial light model in the derivation. The proposed method is effective for both color and gray images with substantial improvement in the process time compared to conventional methods. The proposed method is validated by using simulated synthetic images (color) and real-world underwater images (color and grayscale). Using two underwater image sets acquired from the same area but with different water turbidity, we evaluate the proposed visibility enhancement and camera registration improvement in SLAM.
机译:本文提出了一种有效的水下视觉同时定位和制图(SLAM)的实时可见性增强算法。与空中环境不同,水下环境包含较大的粒子,并且由不同的图像降级模型控制。我们的方法始于对水下粒子物理学的全面了解(例如,向前,向后,多次散射,模糊和噪声)。针对现实应用中的水下图像增强,我们在推导中包括了人造光模型。所提出的方法对于彩色和灰度图像都是有效的,与传统方法相比在处理时间上有实质性的改善。通过使用模拟的合成图像(彩色)和真实世界的水下图像(彩色和灰度)验证了该方法的有效性。使用从相同区域获得的两个水下图像集,但浊度不同,我们评估了SLAM中提议的可见性增强和相机配准改进。

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