DIRSIG digital imaging and remote sensing imaging generation model: Infrared airborne validation & input parameter analysis

The civilian and military need for high resolution infrared imagery has dramatically increased in recent times. Regardless of the user or the need, infrared imagery can provide unique information that is not available in the visible region of the electromagnetic spectrum. Just as the need for real infrared imagery has increased, so has the need for computer generated infrared imagery, also known as synthetic imagery. Synthetic imagery is created by mathematically modeling the real world and the imaging chain, encompassing everything from the target to the sensor characteristics. The amount of faith that can be placed in a synthetic image depends on its accuracy in recreating the real world. The Digital Imaging and Remote Sensing Image Generation Model (DIRSIG) at the Rochester Institute of Technology (RIT) attempts to model the real world. It creates synthetic images through the integration of scene geometry, ray-tracer, thermal, radiometry, and sensor submodels. The focus of this project lies in evaluating the ability of DIRSIG to recreate the imaging chain and produce high resolution synthetic imagery. DIRSIG synthetic imagery of the Kodak Hawkeye plant and the surrounding area was compared to aerial infrared imagery of the same region using root mean square error and rank order correlation. This comparison helped to validate the output from DIRSIG and detect inadequacies in the image chain model. In addition to validating DIRSIG, a procedure for optimizing the input parameters, incorporating a sensitivity analysis, was developed. This reduces the time involved in creating a realistic and accurate synthetic image