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所属单位：自动化学院

发表刊物：SIGNAL PROCESSING-IMAGE COMMUNICATION

关键字：Stereo matching Binocular vision ZNCC Dense disparity map

摘要：Stereo matching is a crucial and challenging step in binocular vision measurement. Robust zero-mean normalized cross-correlation (ZNCC) is widely used for stereo matching. However, direct calculation by using the prevalent ZNCC algorithm is computationally expensive because of the large number of redundancies that directly affect execution time. Therefore, this study proposes a fast method for the reliable computation of the similarity measure through ZNCC for stereo matching. We divide the standard ZNCC function into four independent parts, and this can efficiently reduce computational complexity. Furthermore, a storage strategy is proposed to store calculation results by column and apply a circular queue to the entire matching process. The rapid calculation of the template relies on the position of the pixels in the given image, which is based on the relevant characteristics of adjacent pixels. Invoking the stored calculation template value can help significantly reduce computational complexity. The proposed algorithm was tested on a 2.6-GHz computer with different sizes of images from the Middlebury Stereo Datasets, and the results reveal a remarkably shorter execution time.

ISSN号：0923-5965

是否译文：否

发表时间：2017-03-01

合写作者：Lin, Chuan,Li, Ya,Cao, Yijun

通讯作者：Lin, Chuan,徐贵力