Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

H. A. Camp; Steven Moyer; Richard K. Moore

doi:10.1117/12.851799

22 April 2010 Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

H. A. Camp, Steven Moyer, Richard K. Moore

Author Affiliations +

Proceedings Volume 7662, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXI; 76620A (2010) https://doi.org/10.1117/12.851799
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

Citation Download Citation

H. A. Camp, Steven Moyer, and Richard K. Moore "Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter", Proc. SPIE 7662, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXI, 76620A (22 April 2010); https://doi.org/10.1117/12.851799

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