A FAST OBJECT-TO-IMAGE BEST SCANLINE SEARCH ALGORITHM FOR AIRBORNE LINEAR PUSHBROOM IMAGE PROCESSING

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.