A Robust Ground‐to‐Image Transformation Algorithm and Its Applications in the Geometric Processing of Linear Pushbroom Images

Linear array cameras are widely used in the fields of aerial and space remote sensing. The ground‐to‐image transformation plays a significant role in the geometric processing procedures of linear pushbroom images, which is time‐consuming due to multiple iterative calculations. Moreover, the detectors of the linear array may exhibit a curved shape due to distortions, resulting in a more complex ground‐to‐image transformation. This paper presents a novel ground‐to‐image transformation algorithm for linear pushbroom images based on a rigorous sensor model. We regard the distance between the back‐projected image point and the curved shape linear array as the “generalized distance.” The idea of generalized distance prediction was developed to efficiently determine the best scan line corresponding to the ground point. The plane analytic geometry is employed to solve the practical problems of the ground‐to‐image transformation, including the iterative direction, convergence condition, and subpixel interpolation. The applications of the proposed method in orthorectification and image matching were investigated. The proposed method was comprehensively tested using airborne images, Earth observation satellite images, and planetary images. The experimental results demonstrate that the proposed method (1) delivers high accuracy (better than 1 × 10−4 pixels) and efficiency, (2) is better than the cutting‐edge method based on the geometric constraints of central perspective plane for the linear pushbroom images with distortions, and (3) provides promising applications for generating orthophotos and image matching. The proposed method is easy to implement and efficient, which can greatly enhance the geometric processing abilities for various types of linear pushbroom images.