卢迪, 林雪. 多种相似性测度结合的局部立体匹配算法[J]. 机器人, 2016, 38(1): 1-7. DOI: 10.13973/j.cnki.robot.2016.0001
引用本文: 卢迪, 林雪. 多种相似性测度结合的局部立体匹配算法[J]. 机器人, 2016, 38(1): 1-7. DOI: 10.13973/j.cnki.robot.2016.0001
LU Di, LIN Xue. A Local Stereo Matching Algorithm Based on the Combination of Multiple Similarity Measures[J]. ROBOT, 2016, 38(1): 1-7. DOI: 10.13973/j.cnki.robot.2016.0001
Citation: LU Di, LIN Xue. A Local Stereo Matching Algorithm Based on the Combination of Multiple Similarity Measures[J]. ROBOT, 2016, 38(1): 1-7. DOI: 10.13973/j.cnki.robot.2016.0001

多种相似性测度结合的局部立体匹配算法

A Local Stereo Matching Algorithm Based on the Combination of Multiple Similarity Measures

  • 摘要: 针对立体匹配中匹配代价和支持窗口难以选择的问题,提出一种将多种相似性测度相结合的局部立体匹配算法.首先,构造匹配代价,结合图像的 Census 变换、WLD(Weber 局部描述符)特征、图像色彩信息以及图像梯度信息作为匹配代价;然后,使用引导滤波器对匹配代价进行聚合;最后,针对 WTA(赢者全取)策略引入的视差选择歧义问题和左右一致性检测(LRC)引入的水平条纹问题,提出了一种基于可信度和加权滤波的视差修正算法.利用 Middlebury 测试平台提供的标准测试图像对本文算法进行测试,其平均错误匹配率为 5.30%,与 FastBilateral 算法等一些公认的性能优异算法相比,本文算法提高了匹配准确率.

     

    Abstract: Aiming at the difficulties in choosing matching cost and support window in stereo matching, a local stereo matching algorithm based on the combination of multiple similarity measures is proposed. Firstly, a matching cost is constructed, in which the census transform of image, the WLD (Weber local descriptor) feature of image, the color information of image and the gradient information of image are combined. Secondly, the guided filter is used to aggregate matching cost. Finally, a disparity refinement algorithm based on confidence and weighted filtering is proposed to eliminate the disparity choosing ambiguity brought by WTA (winner take all) strategy and horizontal stripe brought by LRC (left-right consistency) check. The standard test images provided by Middlebury test platform are used to test the proposed algorithm, and the percentage of bad matching pixel is 5.30%. Comparing with some high-performance algorithms, such as FastBilateral algorithm, the proposed method can achieve a higher matching accuracy.

     

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