文章基本信息

标题：A Fast Object-to-Image Best Scanline Search Algorithm for Airborne Linear Pushbroom Image Processing
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作者：Mi Wang ; Fen Hu
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B3b
页码：73-80
出版社：Copernicus Publications
摘要：Airborne linear pushbroom cameras have become one of the most important imaging sensors in today's photogrammetry and remote sensing practices to collect high-resolution multi-channel seamless image strips. The object-to-image coordinate computation is a core step for the process of photogrammetric images. However, for linear pushbroom sensors, each scanline captured by linear sensor owns six exterior orientation parameters (EOPs) at instant of exposure, that is, the image point coordinates will not be accurately calculated through colinearity equations until reasonable EOPs are determined. Therefore the scanline search issue makes object-to-image coordinate transformation computationally intensive during linear pushbroom image processing. This paper presents a fast scanline search algorithm based on the novel Central Perspective Plane of Scanline (CPPS) constraints. The algorithm has the advantage of computational simplicity. According to the CPPS constraints, the best scanline search process can be simply performed through analytical geometric calculations, thus greatly releasing the burden on object-to-image coordinate computation during image processing. The feasibility and robustness of the proposed algorithm are proved through testing two types of airborne linear pushbroom images, acquired by ADS40 and STARIMAGER, respectively. Compared with the traditional mainstream algorithms, the proposed algorithm has considerably saved nearly 70% of the computation time
关键词：Airborne Pushbroom Images; Object-to-image Coordinate Computation; Best Scanline Search; Central Perspective ; Plane of Scanline