Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes program code. Includes bibliographical references (p. 94-96).

Thesis (Ph. D.)--University of Washington, 1998. / Vita. Includes bibliographical references (leaves [99]-106).

With the increased technological advances of thermal imagers, existing theoretical models are not capable of predicting the advantages of advanced thermal imagers. The advanced thermal imager contains a staring focal plane array, which may be sensitive to multiple spectra, and light enough to be mounted on a rifle. Research was conducted to address portions of these three areas. Psychophysical experiments were conducted to model the impact of insufficient sampling on human observer performance for the identification of military vehicles. An information comparison metric was proposed for the comparison of different spectral images. The impact of dead pixels and thermal imager noise on the comparison metric were measured. A human performance model was then developed to predict a humans ability to identify small handheld objects. The impacts of these models on current and future research were discussed.

Thesis (M.S.)--Brigham Young University. Dept. of Mechanical Engineering, 2004. / Includes bibliographical references (p. 103-107).

Thesis--School of Advanced Airpower Studies, Maxwell Air Force Base, Ala., 1993-94. / Title from title screen (viewed Nov. 3, 2003). "April 1995." Includes bibliographical references.

Dissertation (Ph.D.)--Auburn University, 2009. / Abstract. Vita. Includes bibliographic references (p.131-139).

Designers of automatic target recognition algorithms (ATRs) need to compare the performance of different ATRs on a wide variety of imagery. The task would be greatly facilitated by an image complexity metric that correlates with the performance of a large number of ATRs. The ideal metric is independent of any specific ATR and does not require advance knowledge of true targets in the image. No currently used metric meets both these criteria. Complete independence of ATRs and prior target information is neither possible nor desirable since the metric must correlate with ATR performance. An image complexity metric that derives from the common characteristics of a large set of ATRs and the attributes of typical targets may be sufficiently general for ATR comparison. Many real-time, tactical ATRs operate on forward looking infrared (FLIR) imagery and identify, as potential targets, image regions of a specific size that are highly discernible by virtue of their contrast and edge strength. For such ATRs, an image complexity metric could be based on measurements of the mutual discernibility of image regions on various scales. This paper: (1) reviews ATR algorithms in the public domain literature and investigates the common characteristics of both the algorithms and the imagery on which they operate; (2) shows that complexity measurement requires a complete segmentation of the image based on these commonalities; (3) presents a new method of scale-specific image segmentation that uses the mask-driven close-open transform, a novel implementation of a morphological operator; (4) reviews edge detection for discernibility measurement; (5) surveys image complexity metrics in the current literature and discusses their limitations; (6) proposes a new local feature discernibility metric based on relative contrast and edge strength; (7) derives a new global image complexity metric based on the probability distribution of local metrics; (8) compares the metric to the output of a specific ATR; and (9) makes suggestions for further work.

No description available.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (M.S.)--Air Force Institute of Technology, 2008. / AFIT/GOR/ENS/08-22. "March 2008." Title from title page of PDF document (viewed on: Jan. 5, 2009). Includes bibliographical references.