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Proceedings Paper

Automated assessment of video image quality: implications for processing and exploitation
Author(s): John M. Irvine
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Paper Abstract

Several methods have been developed for quantifying the information potential of imagery exploited by a human observer. The National Imagery Interpretability Ratings Scale (NIIRS) has proven to be a useful standard for intelligence, surveillance, and reconnaissance (ISR) applications. Extensions of this approach to motion imagery have yielded a body of research on the factors affecting interpretability of motion imagery and the development of a Video NIIRS. Automated methods for assessing image interpretability can provide valuable feedback for collection management and guide the exploitation and analysis of the imagery. Prediction models that rely on image parameters, such as the General Image Quality Equation (IQE), are useful for conducting sensor trade studies and collection planning. Models for predicting image quality after image acquisition can provide useful feedback for collection management. Several methods exist for still imagery. This paper explores the development of a similar capability for motion imagery. In particular, we propose methods for predicting the interpretability of motion imagery for exploitation by an analyst. A similar model is considered for automated exploitation.

Paper Details

Date Published: 3 May 2012
PDF: 10 pages
Proc. SPIE 8360, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX, 83600J (3 May 2012); doi: 10.1117/12.918969
Show Author Affiliations
John M. Irvine, Charles Stark Draper Lab. (United States)


Published in SPIE Proceedings Vol. 8360:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX
Daniel J. Henry; Davis A. Lange; Dale Linne von Berg; Darrell L. Young; Kenneth L. Bernier; Jeff J. Guell; Sreekanth Danny Rajan, Editor(s)

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