Presentation + Paper
3 May 2017 Progress in sensor performance testing, modeling and range prediction using the TOD method: an overview
Author Affiliations +
Abstract
The Triangle Orientation Discrimination (TOD) methodology includes i) a widely applicable, accurate end-to-end EO/IR sensor test, ii) an image-based sensor system model and iii) a Target Acquisition (TA) range model. The method has been extensively validated against TA field performance for a wide variety of well- and under-sampled imagers, systems with advanced image processing techniques such as dynamic super resolution and local adaptive contrast enhancement, and sensors showing smear or noise drift, for both static and dynamic test stimuli and as a function of target contrast. Recently, significant progress has been made in various directions. Dedicated visual and NIR test charts for lab and field testing are available and thermal test benches are on the market. Automated sensor testing using an objective synthetic human observer is within reach. Both an analytical and an image-based TOD model have recently been developed and are being implemented in the European Target Acquisition model ECOMOS and in the EOSTAR TDA. Further, the methodology is being applied for design optimization of high-end security camera systems. Finally, results from a recent perception study suggest that DRI ranges for real targets can be predicted by replacing the relevant distinctive target features by TOD test patterns of the same characteristic size and contrast, enabling a new TA modeling approach. This paper provides an overview.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Piet Bijl, Maarten A. Hogervorst, and Alexander Toet "Progress in sensor performance testing, modeling and range prediction using the TOD method: an overview", Proc. SPIE 10178, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVIII, 101780U (3 May 2017); https://doi.org/10.1117/12.2266788
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Sensors

Signal to noise ratio

Systems modeling

Electro optical modeling

Data modeling

Performance modeling

Imaging systems

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