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Proceedings Paper

Image compression quality metrics
Author(s): Harold H. Szu; Charles C. Hsu; Joseph Landa; Terry L. Jones; Barbara L. O'Kane; John Desomond O'Connor; Romain Murenzi; Mark J. T. Smith
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Paper Abstract

Battlefield reconnaissance through tactical surveillance video systems requires transmission of images through a limited bandwidth and capacity to achieve aided target recognition (ATR), of which some lossy compression is indispensable. Based on available resolution, ATR can have three functionality goals: (1) detection of a target, (2) recognition of target classes, and (3) identification of individual target membership. Thus, it is desirable to build an intelligent lookup table which maps a specific ATR goal into an appropriate image compression. Such a table may be built implicitly be employing the exemplar training procedure of artificial neutral networks. In order to illustrate this concept, we will introduce a computational metric called feature persistence measure, useful for x-ray luggage inspections, and further generalized here to capture human performance in a tactical imaging scenario.

Paper Details

Date Published: 3 April 1997
PDF: 14 pages
Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271768
Show Author Affiliations
Harold H. Szu, Naval Surface Warfare Ctr. (United States)
Charles C. Hsu, Trident Systems Inc. (United States)
Joseph Landa, Trident Systems Inc. (United States)
Terry L. Jones, U.S. Army Night Vision & Electronic Sensor Directorate (United States)
Barbara L. O'Kane, U.S. Army Night Vision & Electronic Sensor Directorate (United States)
John Desomond O'Connor, E-OIR Measurements (United States)
Romain Murenzi, Clark Atlanta Univ. (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3078:
Wavelet Applications IV
Harold H. Szu, Editor(s)

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