Visual acuity, contrast sensitivity, and range performance with compressed motion video

Bijl, Piet

doi:10.1117/1.3503950

Cited by 13 publications

(1 citation statement)

References 19 publications

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“…From the TOD target acquisition model 7 , field range can be predicted from the TOD curve as a function of the target size, the task level required (Detection, Recognition or Identification of the target) at a given probability, the visibility through the atmosphere and the illumination level. Figure 12 shows an example: Figure 12.…”

Section: Range Prediction Examplesmentioning

confidence: 99%

Performance characterization of night vision equipment based on triangle orientation discrimination (TOD) methodology

Nicolas

Lejard²,

Deltel

et al. 2013

SPIE Proceedings

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Night vision equipment is crucial in order to accomplish supremacy and safety of the troops on the battlefield. Evidently, system integrators, MODs and end-users need access to reliable quantitative characterization of the expected field performance when using night vision equipment. The Image Intensifier tube is one of the most important engines driving the performance for night vision equipment. As a major tube manufacturer, PHOTONIS has investigated the link between its products physical design parameters and the actual end-user field performance. The developments include 1) an end-to-end performance measurement method and test facility, 2) an image-based night vision simulation and 3) a range estimation model. The purpose is twofold: i) being able to support the need of the integrators and end users, and ii) further systematic improvement of night vision equipment design. For the end-to-end test, PHOTONIS and TNO cooperated in the implementation of the TOD (Triangle Orientation Discrimination) test for night vision equipment. This test provides a clear and rigorous ranking of the products with respect to their target acquisition performance level. With respect to the image-based simulation, PHOTONIS performs physical and performance comparisons between artificial and real imagery, promising exciting further development of a model based on the merging of the different approaches of night vision evaluation and modelling. In this paper, we present the PHOTONIS night vision test laboratory, provide TOD results for a set of night vision devices and show range prediction examples.

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Section: Range Prediction Examplesmentioning

confidence: 99%

Performance characterization of night vision equipment based on triangle orientation discrimination (TOD) methodology

Nicolas

Lejard²,

Deltel

et al. 2013

SPIE Proceedings

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Bayesian Contrast Measures and Clutter Distribution Determinants of Human Target Detection

Novak

Armstrong

Caelli

et al. 2017

IEEE Trans. on Image Process.

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Human target detection is known to be dependent on a number of components: one, basic electro-optics including image contrast, the target size, pixel resolution, and contrast sensitivity; two, target shape, image type and features, types of clutter; and three, context and task requirements. Here, we consider a Bayesian approach to investigating how these components contribute to target detection. To this end, we develop and compare three different formulations for contrast: mean contrast, perceptual contrast, and a Bayesian-based histogram contrast statistic. Results on past detection data show how the latter contrast measure correlates well with human performance factoring out all other dimensions. As for clutter, our findings show that with large targets, there are effectively no clutter effects. Furthermore, clutter does not have a major effect on detection when it is not contiguous with the target even when it is smaller. However, except for large targets, when the target is contiguous with the clutter, detection clearly decreases as a function of the similarity of target and clutter features-creating type of "clutter camouflage". This Bayesian formulation uses priors based on the contrast histogram statistics derived from all the images, the image context, and implies that human observers have adapted their criteria to fit with the image set, context, and task.

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Performance characterization of night vision equipment based on the triangle orientation discrimination methodology

Nicolas

Bijl²,

Deltel

2015

Opt. Eng

Self Cite

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Night vision equipment is crucial in order to accomplish supremacy and safety of the troops on the battlefield. Evidently, system integrators, ministry of defenses and end-users need access to reliable quantitative characterization of the expected field performance when using night vision equipment. The image intensifier tube is one of the most important engines driving the performance for night vision equipment. As a major tube manufacturer, Photonis investigates the link between its products' physical design parameters and the actual end-user field performance. The developments include (1) an end-to-end performance measurement method and test facility, (2) an image-based night vision simulation, and (3) a range estimation model. The purpose is twofold:(1) being able to support the need of the integrators and end-users and (2) further systematic improvement of night vision equipment design. For the end-to-end test, Photonis and TNO cooperated in the implementation of the triangle orientation discrimination (TOD) test for night vision equipment. This test provides a clear and rigorous ranking of the products with respect to their target acquisition performance level. We present the Photonis night vision test laboratory, provide TOD results for a set of night vision devices, and show range prediction examples.

show abstract

Visual acuity, contrast sensitivity, and range performance with compressed motion video

Cited by 13 publications

References 19 publications

Performance characterization of night vision equipment based on triangle orientation discrimination (TOD) methodology

Performance characterization of night vision equipment based on triangle orientation discrimination (TOD) methodology

Bayesian Contrast Measures and Clutter Distribution Determinants of Human Target Detection

Performance characterization of night vision equipment based on the triangle orientation discrimination methodology

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