&lt;title&gt;Capturing the sampling effects: a TOD sensor performance model&lt;/title&gt;

Hogervorst, Maarten A.; Bijl, Piet; Valeton, J. M.

doi:10.1117/12.439162

Cited by 30 publications

(30 citation statements)

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“…This can be understood afterwards but might have been unnoticed for a long time without doing a test. Third, a test may be used to optimize or tune the parameters of the algorithm for specific sensor, preferably in combination with a vision model 18,19 . In our case, we may use the recordings from this study over and over again to test new algorithms.…”

Section: Discussionmentioning

confidence: 99%

Applicability of TOD, MTDP, MRT and DMRT for dynamic image enhancement techniques

Bijl¹,

Schutte²,

Hogervorst³

2006

Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVII

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Current end-to-end sensor performance measures such as the TOD, MRT, DMRT and MTDP were developed to describe Target Acquisition performance for static imaging. Recent developments in sensor technology (e.g. microscan) and image enhancement techniques (e.g. Super Resolution and Scene-Based Non-Uniformity Correction) require that a sensor performance measure can be applied to dynamic imaging as well. We evaluated the above-mentioned measures using static, dynamic (moving) and different types of enhanced imagery of thermal 4-bar and triangle tests patterns. Both theoretical and empirical evidence is provided that the bar-pattern based methods are not suited for dynamic imaging. On the other hand, the TOD method can be applied easily without adaptation to any of the abovementioned conditions, and the resulting TOD data are in correspondence with the expectations. We conclude that the TOD is the only current end-to-end measure that is able to quantify sensor performance for dynamic imaging and dynamic image enhancement techniques.

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Section: Discussionmentioning

confidence: 99%

Applicability of TOD, MTDP, MRT and DMRT for dynamic image enhancement techniques

Bijl¹,

Schutte²,

Hogervorst³

2006

Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVII

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“…The relationship with real target acquisition was validated in several experiments 7,8 . Recently a TOD sensor model 9 was developed that explicitly takes into account non-linear operations such as sampling. It calculates a TOD curve by end-to-end simulation: a sensor model calculates the images of a set of input test patterns.…”

Section: Introductionmentioning

confidence: 99%

TOD, NVTherm, and TRM3 model calculations: a comparison

2002

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At the moment there are three potential models and associated measures to replace the FLIR92 model and the MRTD as the standard for sensor performance characterization and TA range predictions. These are: 1) the NVTherm model that calculates the MRTD-ID, 2) the TRM3 model that calculates the MTDP and 3) the TOD model that calculates the TOD. The three models are grossly different in theoretical approach. We ran the models for the same set of hypothetical cameras. As default sensor, we used a 'typical' under-sampled Focal Plane Array camera. Then, we independently varied the pre-and post-filter MTF's over a wide range while keeping the sampling frequency fixed so that the cameras ranged between well-sampled and highly undersampled. The differences in outcome are striking. For example, for a range of sensors around the default the TOD model predicts that performance is determined primarily by the sampling frequency, while NVTherm predicts that pre-an post-filter blur dominate in this region. The results with TRM3 are surprising: the model predicts that increasing image information content by applying microscan to the default sensor, decreases predicted TA performance. The origin lies in the use of the periodic four-bar test pattern and the definition of the MTDP. In the low contrast region, the MTDP and the TOD are similar but the MRTD-ID deviates from these two. The MTDP and MRTD-ID are different even in the well-sampled region where they both should be equivalent to the conventional MRTD. The study shows that the choice of a model has a large impact on sensor design decisions or trade-offs between sensors. The TOD method is the most general of the three approaches and has the strongest basis. Until now, validation of the model predictions is very limited. Therefore, a joint TA performance study with simulated sensors (e.g. those used in the present study) and target contrast as variables would be very useful.

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“…Exactly the same procedure is used in the TOD, where the observer has to choose which of four possible triangle orientations was presented (see section 4.6). An nAFC procedure also has advantages for modeling and automatic measurement 9,10 (see section 3.3).…”

Section: 11mentioning

confidence: 99%

<title>Critical evaluation of test patterns for EO system performance characterization</title>

2001

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The traditional test pattern for end-to-end EO system performance testing in the laboratory has been the static 3-or 4-bar target. This choice was governed by linear systems approach. The introduction of undersampled imagers such as IRFPAs (infrared focal plane array cameras) has challenged the testing community to develop an alternative test, because the occurrence of aliasing has a completely different effect on periodic targets (such as the bar target) and real, non-periodic targets. A new test should at least have the following properties: lab testing is objective and easy, the measure is representative for field performance, and modeling (sensor and human) the test should be relatively easy. Several alternative test methods and test patterns have already been proposed. An example is the TOD method that uses nonperiodic test patterns. Other examples are the dynamic MRT that uses a moving 4-bar target, and the MTDP that uses the traditional static target but allows that not all four bars have to be present in the image. The development of real-time scene projection allows testing with real infrared targets under controlled conditions. The authors will discuss a large number of test patterns and methods and show their advantages and disadvantages for end-to-end EO system performance testing. They conclude that simple non-periodic spatial test patterns, such as used in the TOD, are the best choice for sensor performance characterization.Keywords: Electro-Optical system performance testing, TOD, MRTD, Dynamic MRT, MTDP INTRODUCTIONA standard laboratory test to determine human performance with Electro-Optical (EO) viewing systems is required for several purposes, e.g. (i) to verify if a sensor is working properly, (ii) to compare competing sensor systems, (iii) to verify if a new type of sensor meets the expectations based on its design, or (iv) to predict field performance. Field performance can be target acquisition (TA) performance in a military or a civilian environment (security), or reading performance with the unaided eye for example.Basically, there are two approaches for such a test. The first is to measure essential physical parameters of the sensor system or parts of the system (e.g. the MTF or the NETD), and then use a model to predict human performance. However, this requires a thorough understanding of human vision with sensors, and current vision models are not sophisticated enough to cope with all target and sensor factors that affect visual performance.The second approach is to measure end-to-end sensor performance including the human observer. It is often not very practical (or even possible) to perform such measurements for a real task in a real situation. Therefore, laboratory Sensor Performance Measures (such as the MRTD 1 ) have been introduced. In the laboratory, circumstances can be controlled and measurements can be performed quicker, easier, and with higher accuracy. It is obvious that the results of such a lab test need to be representative for the corresponding tasks in the fie...

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<title>Capturing the sampling effects: a TOD sensor performance model</title>

Cited by 30 publications

References 10 publications

Applicability of TOD, MTDP, MRT and DMRT for dynamic image enhancement techniques

Applicability of TOD, MTDP, MRT and DMRT for dynamic image enhancement techniques

TOD, NVTherm, and TRM3 model calculations: a comparison

<title>Critical evaluation of test patterns for EO system performance characterization</title>

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