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A new stereo matching algorithm based on image segmentation

机译:一种新的基于图像分割的立体匹配算法

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摘要

Comparing with the local algorithm in stereo matching, the global algorithm can get highly quality disparity space image (DSI) usually. The graph cuts algorithm, as the traditional global matching method, can get the highly quality DSI with long computation time, so the graph cuts algorithm is difficult to used in real-time matching applications. In this paper, a new method is proposed to accelerate the matching speed. Firstly, the segments of the image are calculated using the Gaussians pyramid (DoGs) computing method, secondly calculate the disparity range of two corresponding image segments in image pair using the color feature, and every segment pair is matched based on graph cuts algorithm according to the offset of disparity range in parallel time, finally all the segments are assembled into a whole disparity image. The experimental results show that the matching speed is accelerated greatly with a high disparity image quality.
机译:与立体匹配中的局部算法相比,全局算法通常可以获得高质量的视差空间图像(DSI)。作为传统的全局匹配方法,图割算法可以得到高质量的DSI,且计算时间较长,因此图割算法很难用于实时匹配应用中。本文提出了一种加快匹配速度的新方法。首先,使用高斯金字塔(DoGs)计算方法计算图像的片段,然后使用颜色特征计算图像对中两个对应图像片段的视差范围,然后根据图割算法根据在平行时间上视差范围的偏移,最后将所有片段组装成一个完整的视差图像。实验结果表明,匹配速度大大提高,图像质量较高。

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