Sifting out point matches for high buildings in multiview very-high-resolution urban remote sensing images under local translation transformation

Lei Hu; Yongmei Zhang; Yunjun Yu; Yun Zhang

doi:10.1117/1.JRS.13.016523

14 March 2019 Sifting out point matches for high buildings in multiview very-high-resolution urban remote sensing images under local translation transformation

Lei Hu, Yongmei Zhang, Yunjun Yu, Yun Zhang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 13, Issue 1, 016523 (March 2019). https://doi.org/10.1117/1.JRS.13.016523

Abstract

In multitemporal very-high-resolution urban remote sensing images, buildings, especially high-rise buildings, show difference in terms of morphology due to the different view angles. In the coregistered images, the pixels of the same building are not corresponding to each other, which causes false alarm in change detection. Our objective is to find out the matching points located on the roofs of high-rise buildings. When the difference of view angle between the coregistered images is fixed, we discover that there are spatial translation relationships, i.e., local translation transformation and fixed angle offset, between the point matches of high-rise building roofs. Therefore, using these relationships, a method that can sift out point matches of roofs to their correct positions is proposed. The experimental results show that most point matches located on the roof of the same building can be fast and correctly sifted out.

Citation Download Citation

Lei Hu, Yongmei Zhang, Yunjun Yu, and Yun Zhang "Sifting out point matches for high buildings in multiview very-high-resolution urban remote sensing images under local translation transformation," Journal of Applied Remote Sensing 13(1), 016523 (14 March 2019). https://doi.org/10.1117/1.JRS.13.016523

Received: 10 October 2018; Accepted: 21 February 2019; Published: 14 March 2019

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