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Improved Stereo Vision of Indoor Dense Suspended Scatterers Scenes from De-scattering Images

机译:通过解散图像改善室内密集悬浮散射体场景的立体视觉

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Stereo vision is important in robotics since retrieving depth is very necessary in many robotics applications. Most of state-of-the-art stereo vision algorithms solve the problem with clear images but not the images corrupted by scattering. In this paper, we propose the stereo vision system for robot working in dense suspended scatterers environment. The imaging model of images taken in the environment under active light source based on single scattering phenomenon is analyzed. Based on that, scattering signal can be removed from images. The recovered images are then used as input image for stereo vision. The proposed method is then evaluated based on quality of stereo depth map.
机译:立体视觉在机器人技术中很重要,因为在许多机器人应用中,获取深度非常必要。大多数最新的立体视觉算法都可以用清晰的图像解决问题,但不能解决因散射而损坏的图像。在本文中,我们提出了用于在密集悬浮散射体环境中工作的机器人的立体视觉系统。分析了基于单一散射现象在有源光源环境下拍摄的图像的成像模型。基于此,可以从图像中去除散射信号。然后将恢复的图像用作立体视觉的输入图像。然后根据立体深度图的质量对提出的方法进行评估。

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