Video National Imagery Interpretability Rating Scale criteria survey results

Young, Darrell; Yen, James H.; Petitti, Fred; Bakir, Tariq; Brennan, Michelle; Butto, Robert

doi:10.1117/12.816546

Cited by 11 publications

(8 citation statements)

References 6 publications

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“…VNIIRS definitions extend from NIIRS as shown by Young, et al [46]. Table 2 lists some of the relations between the NIIRS and VNIIRS levels.…”

Section: Vniirs Definitionsmentioning

confidence: 98%

“…VNIIRS has many developments with a key focus of this paper using the work of Young, et al [46,47] and the Motion Imagery Quality Equation (MIQE). Initial derivations were done by Irvine et al [48,49,50,51] to lay a foundation for a motion imagery quality metric that utilized the NIIRS ground sampling distance.…”

Section: Vniirsmentioning

confidence: 99%

“…from: Young, D., et al, "Video National Imagery Interpretability Rating Scale criteria survey results," Proc SPIE, (2009)[46] …”

mentioning

confidence: 99%

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Application of VNIIRS for target tracking

Blasch¹,

Kahler²

2015

SPIE Proceedings

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The Motion Imagery Standards Board (MISB) has created the Video National Imagery Interpretability Rating Scale (V-NIIRS). VNIIRS extends NIIRS to scene characterization from streaming video to include object recognition of various targets for a given size. To apply VNIIRs for target tracking, there is a need to understand the operating conditions of the sensor type, environmental phenomenon, and target behavior (SET). In this paper, we explore VNIIRS for target tracking given the sensor resolution to support the relative tracking performance using track success. The relative assessment can be used in relation to the absolute target size associated with the VNIIRS. In a notional analysis, we determine the issues and capabilities of using VNIIRS video quality ratings to determine track success. The outcome of the trade study is an experiment to understand how to use VNIIRS can support target tracking evaluation.

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“…VNIIRS definitions extend from NIIRS as shown by Young, et al [46]. Table 2 lists some of the relations between the NIIRS and VNIIRS levels.…”

Section: Vniirs Definitionsmentioning

confidence: 98%

Section: Vniirsmentioning

confidence: 99%

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Application of VNIIRS for target tracking

Blasch¹,

Kahler²

2015

SPIE Proceedings

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“…The most effective way of measuring image quality is human observation [32], because the purpose of the image is to convey information to a human observer -such as the Video National Imagery Interpretability Rating Scale (V-NIIRS) [33,34]. Unfortunately, current methods have inconvenient metrics in the field of image processing because these processes have yet to be fully automated [35].…”

Section: Introductionmentioning

confidence: 99%

Multi-focus and multi-modal fusion: a study of multi-resolution transforms

et al. 2016

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Automated image fusion has a wide range of applications across a multitude of fields such as biomedical diagnostics, night vision, and target recognition. Automation in the field of image fusion is difficult because there are many types of imagery data that can be fused using different multi-resolution transforms. The different image fusion transforms provide coefficients for image fusion, creating a large number of possibilities. This paper seeks to understand how automation could be conceived for selected the multiresolution transform for different applications, starting in the multifocus and multi-modal image sub-domains. The study analyzes the greatest effectiveness for each sub-domain, as well as identifying one or two transforms that are most effective for image fusion. The transform techniques are compared comprehensively to find a correlation between the fusion input characteristics and the optimal transform. The assessment is completed through the use of no-reference image fusion metrics including those of information theory based, image feature based, and structural similarity based methods.

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“…Building on these perceptions studies, a new Video NIIRS was developed Young et al 2009). The work presented in this paper quantifies video interpretability using a 100-point scale described in Section 3 (Irvine et al 2007a;Irvine et al 2007b;Irvine et al 2007c).…”

Section: Image Interpretabilitymentioning

confidence: 99%