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Robust Automatic Generation of True Orthoimages From Very High-Resolution Panchromatic Satellite Imagery Based on Image Incidence Angle for Occlusion Detection

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Orthoimages have proven to provide useful reference data for a variety of geospatial applications. Their improved versions, true orthoimages, are even more valuable as they have been adjusted also for… Click to show full abstract

Orthoimages have proven to provide useful reference data for a variety of geospatial applications. Their improved versions, true orthoimages, are even more valuable as they have been adjusted also for high objects. Even though true orthoimages have been—over the last decades—generated mainly from aerial images, we believe there is a need to produce true orthoimages also from satellite images. The aim of this article is to present the already developed automatic procedure for generating true orthoimages from very high-resolution optical satellite images. The automatic workflow consists of five modules, starting with the extraction of ground control points, through the geometric processing of image blocks, occlusion detection, orthorectification, and finally the generation of true orthoimages. The orthorectification module uses a high-resolution digital surface model derived from laser scanning data. Occlusion detection is performed using a ray-tracing method based on the incidence angle, which is suitable for images acquired by satellites and processed with rational function models. The usability of the workflow was demonstrated with the test of six Pléiades images that were acquired on different dates and with different viewing angles. The research presents the accuracy of the geometric correction and the quality of the true orthoimage generated with different numbers of images. The results show that satellite-based true orthoimages are suitable for the extraction of spatial information that can be used directly by the end-users.

Keywords: occlusion detection; orthoimages high; true orthoimages; high resolution

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2021

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