A Fast Photogrammetric Processing Method for Linear Pushbroom Planetary Remote Sensing Images

GENG Xun1,2, XU Qing3

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Journal of Deep Space Exploration ›› 2022, Vol. 9 ›› Issue (3) : 348-356. DOI: 10.15982/j.issn.2096-9287.2022.20210002
Topic:Mapping technique of extraterrestrial planets

A Fast Photogrammetric Processing Method for Linear Pushbroom Planetary Remote Sensing Images

  • GENG Xun1,2, XU Qing3
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Abstract

Planetary photogrammetry is widely used to derive the mapping products of extraterrestrial planets. However, the existing planetary photogrammetric methods exhibit low efficiency and poor applicability for long strip linear pushbroom planetary images. We developed photogrammetric processing method as well as corresponding software modules for linear pushbroom planetary images based on fast geometric rectification. Based on the rigorous sensor model of linear pushbroom planetary images, the fast back projection algorithm is used for orthophotos rectification, and multi-threaded programming technique is also used to further improve the computational efficiency. To derive control network for linear pushbroom planetary images with large amount of data, we first conduct image matching on approximate orthophotos that derived from fast geometric rectification to acquire tie points, and then convert the matched tie points into original image space using rigorous sensor model. Experiments were conducted using Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) and Mars Express (MEX) Hight Resolution Stereo Camera (HRSC) images, and the corresponding DOMs and DEMs were derived. Compared with the planetary image processing software USGS ISIS, the developed method significantly improves the processing efficiency of linear pushbroom planetary images.

Keywords

planetary photogrammetry / lunar mapping / Mars mapping / geometric processing

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GENG Xun, XU Qing. A Fast Photogrammetric Processing Method for Linear Pushbroom Planetary Remote Sensing Images. Journal of Deep Space Exploration, 2022, 9(3): 348‒356 https://doi.org/10.15982/j.issn.2096-9287.2022.20210002

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