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'DVS Image' Noise Removal Using K-SVD Method

机译：使用K-SVD方法去除'DVS图像'噪声

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摘要

Dynamic Vision Sensor (DVS) is an event-based camera, which captures the changing pixel of vision. It captures the scene in the form of events. In this paper, we use a unique approach to visualize the events DVS captures with "DVS images". DVS is sensitive enough to capture objects moving in high speed, but noise is also captured. In order to improve the quality, we remove the noise of those images. Different from traditional images, the noise and objects in "DVS images" are both composed of distributed points. It is hard to use traditional methods to remove the noise. This paper proposes an efficient approach for "DVS image" noise removal. It is based on K-SVD algorithm and we improve the algorithm according to certain applications. The proposed framework can deal with "DVS images" containing different amount of noise. Experiments show that the proposed method can work well both on a fixed DVS and a moving DVS.
机译：动态视觉传感器（DVS）是基于事件的摄像机，可捕获变化的视觉像素。它以事件的形式捕获场景。在本文中，我们使用一种独特的方法来可视化DVS通过“ DVS图像”捕获的事件。 DVS足够灵敏，可以捕获高速移动的对象，但是也可以捕获噪声。为了提高质量，我们去除了这些图像的噪点。与传统图像不同，“ DVS图像”中的噪声和对象均由分布点组成。很难使用传统方法来消除噪音。本文提出了一种有效的“ DVS图像”噪声去除方法。它基于K-SVD算法，并且根据某些应用对算法进行了改进。所提出的框架可以处理包含不同数量的噪声的“ DVS图像”。实验表明，该方法在固定式DVS和移动式DVS上均可很好地工作。

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