Image compression quality metrics
Harold H Szu, Charles Chia-chuen Hsu, Joseph S. Landa, Terry L. Jones, Barbara L. O’Kane, John D. O’Connor, Romain Murenzi, Mark J. T. Smith · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
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.