Visual performance-based image enhancement methodology: an investigation of contrast enhancement algorithms

Kelly E. Neriani; Travis J. Herbranson; George A. Reis; Alan R. Pinkus; Charles D. Goodyear

doi:10.1117/12.666018

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19 May 2006 Visual performance-based image enhancement methodology: an investigation of contrast enhancement algorithms

Kelly E. Neriani, Travis J. Herbranson, George A. Reis, Alan R. Pinkus, Charles D. Goodyear

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Proceedings Volume 6226, Enhanced and Synthetic Vision 2006; 622606 (2006) https://doi.org/10.1117/12.666018
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

While vast numbers of image enhancing algorithms have already been developed, the majority of these algorithms have not been assessed in terms of their visual performance-enhancing effects using militarily relevant scenarios. The goal of this research was to apply a visual performance-based assessment methodology to evaluate six algorithms that were specifically designed to enhance the contrast of digital images. The image enhancing algorithms used in this study included three different histogram equalization algorithms, the Autolevels function, the Recursive Rational Filter technique described in Marsi, Ramponi, and Carrato¹ and the multiscale Retinex algorithm described in Rahman, Jobson and Woodell². The methodology used in the assessment has been developed to acquire objective human visual performance data as a means of evaluating the contrast enhancement algorithms. Objective performance metrics, response time and error rate, were used to compare algorithm enhanced images versus two baseline conditions, original non-enhanced images and contrast-degraded images. Observers completed a visual search task using a spatial-forcedchoice paradigm. Observers searched images for a target (a military vehicle) hidden among foliage and then indicated in which quadrant of the screen the target was located. Response time and percent correct were measured for each observer. Results of the study and future directions are discussed.

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Kelly E. Neriani, Travis J. Herbranson, George A. Reis, Alan R. Pinkus, and Charles D. Goodyear "Visual performance-based image enhancement methodology: an investigation of contrast enhancement algorithms", Proc. SPIE 6226, Enhanced and Synthetic Vision 2006, 622606 (19 May 2006); https://doi.org/10.1117/12.666018

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