Efficient registration of aerial video to geo-referenced images

Shubin Zhao

doi:10.1117/12.2572905

12 June 2020 Efficient registration of aerial video to geo-referenced images

Shubin Zhao

Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 1151915 (2020) https://doi.org/10.1117/12.2572905
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan

Abstract

Airborne surveillance and reconnaissance play an increasingly crucial role in military operations. Aerial video can perceive dynamic events, track active targets and provide the real-time location of targets, but the poor accuracy of geographical coordinates limits its usefulness. Registration of aerial video to geo-referenced images is an effective means to improve the location accuracy. Generally, the aerial video and the geo-referenced images to be registered were taken at different times, from different viewpoints and by different cameras. Due to these differences, registration of aerial video to geo-referenced images is a challenging task. This paper discusses the essential issues of the problem, analyzes the characteristics of the images, and shows what features work better. Then, this paper presents a two-stage image registration algorithm, which is based on decomposition of transformation space. The first stage estimates the rotation parameter by matching histograms of weighted edge orientation between aerial image and geo-referenced image. The second stage determines the translation parameters by comparing partial images using partial Hausdorff distance. This approach is computationally efficient and robust to significant differences between the images to be aligned. Experiments have been conducted on real-world data, and the results have shown the good performance of the algorithm.

Citation Download Citation

Shubin Zhao "Efficient registration of aerial video to geo-referenced images", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 1151915 (12 June 2020); https://doi.org/10.1117/12.2572905

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