Comparison of the components and the overall fidelity of infrared synthetic image generation models with truth data and imagery is a crucial part of determining model validity and identifying areas in which improvements can be made. The Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation Model, DIRSIG, was validated in the midwave infrared (MWIR) and longwave infrared (LWIR) regions using measured meteorological, material, and radiometric data. Error propagation techniques clearly defmed areas where improvements to the model could be made (e.g. inclusion of clouds). An overall comparison of truth and synthetic images yields RMS errors of as low as 1.8°C for actual temperature, and 5°C (LWIR) and 6°C (MWIR) for apparent temperatures. Analysis of rank order correlation statistic shows a very high correlation between brightness rank for object in the truth and DIRSIG images for most times of day.

Date of creation, presentation, or exhibit



"Validation of contrast and phenomenology in the Digital Imaging and Remote Sensing (DIRS) lab's image generation (DIRSIG) model," Proceedings of the SPIE, Infrared Technology XX, Vol. 2269. The International Society of Optical Engineers. Held in San Diego, California: July 1994. This paper is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The authors would like to thank Ms. Carolyn Kitchen for preparation of this paper and Mr. Frank Tantalo for his work on data reduction. We also gratefully acknowledge the support of the Central Intelligence Agency for their support of this effort. Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Conference Proceeding

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


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