Multisource Data Processing for Semi-Automated Radiometrically-Correct Scene Simulation
The digital imaging and remote sensing image generation (DIRSIG) model is an established, first-principles based scene simulation tool that produces synthetic multi-spectral and hyperspectral images from the visible to long wave infrared (0.4 to 20 microns). Significant enhancements such as spectral polarimetric and active light detection and ranging (lidar) models have also been incorporated into the software, providing an extremely powerful tool for algorithm testing and sensor evaluation. However, the extensive time required to create large-scale scenes has limited DIRSIG's ability to generate scenes "on demand." To date, scene generation has been a laborious, time-intensive process, as the terrain model, CAD objects and background maps have to be created and attributed manually. To shorten the time required for this process, we have initiated a research effort that aims to reduce the man-in-the-loop requirements for several aspects of synthetic hyperspectral scene construction. Through a fusion of 3D lidar data with passive imagery, we are working to semi-automate several of the required tasks in the creation of high-resolution urban DIRSIG scenes. This paper reports on the progress made thus far in achieving these objectives.