Real Time Orthorectification of High Resolution Airborne Pushbroom Imagery

摘要

Advanced architectures have been proposed for efficient orthorectification of digital airborne camera images, including a system based on GPU processing and distributed computing able to geocorrect three digital still aerial photographs per second. Here, we address the computationally harder problem of geocorrecting image data from airborne pushbroom sensors, where each individual image line has associated its own camera attitude and position parameters. Using OpenGL and CUDA interoperability and projective texture techniques, originally developed for fast shadow rendering, image data is projected onto a Digital Terrain Model (DTM) as if by a slide projector placed and rotated in accordance with GPS position and inertial navigation (IMU) data. Each line is sequentially projected onto the DTM to generate an intermediate frame, consisting of a unique projected line shaped by the DTM relief. The frames are then merged into a geometrically corrected georeferenced orthoimage. To target hyperband systems, avoiding the high dimensional overhead, we deal with an orthoimage of pixel placeholders pointing to the raw image data, which are then combined as needed for visualization or processing tasks. We achieved faster than real-time performance in a hyperspectral pushbroom system working at a line rate of 30 Hz with 200 bands and 1280 pixel wide swath over a 1 m grid DTM, reaching a minimum processing speed of 356 lines per second (up to 511 lps), over eleven (up to seventeen) times the acquisition rate. Our method also allows the correction of systematic GPS and/or IMU biases by means of 3D user interactive navigation.