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13 May 2019 Modeling and assessing VNIIRS using in-scene metrics
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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
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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
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