Modeling and assessing VNIIRS using in-scene metrics

John M. Irvine; Charles A. McPherson Sr.; Andrew Kalukin; Gary Takis; James Miller

doi:10.1117/12.2520090

13 May 2019 Modeling and assessing VNIIRS using in-scene metrics

John M. Irvine, Charles A. McPherson Sr., Andrew Kalukin, Gary Takis, James Miller

Proceedings Volume 10992, Geospatial Informatics IX; 1099205 (2019) https://doi.org/10.1117/12.2520090
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

The Video National Imagery Interpretability Rating Scale (VNIIRS) is a useful standard for quantifying the interpretability of motion imagery. Automated accurate assessment of VNIIRS would benefit operators by characterizing the potential utility of a video stream. For still, visible-light imagery the general image quality equation (GIQE) provides a standard model to automatically estimate the NIIRS of the image using sensor parameters, namely the ground sample distance (GSD), the relative edge response (RER), and signal-to-noise ratio (SNR). Typically, these parameters are associated with a specific sensor and the metadata correspond to specific image acquisition. For many tactical video sensors however, these sensor metadata are not available and it is necessary to estimate these parameters from information available in the imagery. We present methods for estimating the RER and SNR through analysis of the scene, i.e. the raw pixel data. By estimating the RER and SNR directly from the video data, we can compute accurate VNIIRS estimates for the video. We demonstrate the method on a set of video data.

Conference Presentation

Citation Download Citation

John M. Irvine, Charles A. McPherson Sr., Andrew Kalukin, Gary Takis, and James Miller "Modeling and assessing VNIIRS using in-scene metrics ", Proc. SPIE 10992, Geospatial Informatics IX, 1099205 (13 May 2019); https://doi.org/10.1117/12.2520090

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available