HIGH PERFORMANCE GCP-BASED PARTICLE SWARM OPTIMIZATION OF ORTHORECTIFICATION OF AIRBORNE PUSHBROOM IMAGERY

We present an evolutionary method for Ground Control Point-based nonlinear registration of airborne pushbroom imagery, based on an implementation of Particle Swarm Optimization (PSO). The proposed method uses previous work for real-time GPU-based geocorrection of airborne pushbroom imagery. By projecting each acquired line onto a Digital Terrain Model (DTM) from the position and attitude of the camera at the time of acquisition, an orthoimage is generated. Using geocorrection as optimization function, the speed achieved allows using evolutionary methods in feasible time, enabling hundreds of repeated approximations during rectification, in contrast to classical geocorrection methods. In our approach, taking advantage of the speed and parallelization of Graphic Processing Units (GPU) by means of CUDA, PSO is used to find the best match between the projected pixels and a number of Ground Control Points, compensating any systematic errors in the navigation data used for the generation of the orthoimage.