A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

Daniel J. Jobson; Zia-ur Rahman; Glenn A. Woodell; Glenn D. Hines

doi:10.1117/12.664591

12 May 2006 A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

Daniel J. Jobson, Zia-ur Rahman, Glenn A. Woodell, Glenn D. Hines

Author Affiliations +

Proceedings Volume 6246, Visual Information Processing XV; 624601 (2006) https://doi.org/10.1117/12.664591
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally within the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging-terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on the limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

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Daniel J. Jobson, Zia-ur Rahman, Glenn A. Woodell, and Glenn D. Hines "A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes", Proc. SPIE 6246, Visual Information Processing XV, 624601 (12 May 2006); https://doi.org/10.1117/12.664591

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