Low light night vision systems based on I2 tubes have been expanding rapidly over the past few years, due to a combination of the growing advancement of this technology and the increased pressure in the current climate. The design of a single optical bench able to fully characterize night vision devices is presented into this paper, focused more specifically on spot defects and goggle axes parallelism tests. These criteria are indeed very important: misalignment between the two binocular images may be one source of visual fatigue and could degrade task performance of the night vision user, and spot defects can act as visual distractions and may be large enough to mask critical information pilots need to conduct normal night vision operations. Thanks to HGH’s IRCOL bench, these two tests are integrated on the same support. Spot defect measurement utilizes machine vision algorithms to determine the size and location of the defects, and the parallelism measurement identifies the angular misalignment between the two channels under test. The spot defect test has also been completely automatized compared to the only visible test previously available All these results will be compiled and directly integrated into a computer-generated report that can be easily used for quality control or for maintenance applications.
Modulating Transfer Function (MTF) has always been very important and useful for objectives quality definition and focal plane settings. This measurand provides the most relevant information on the optimized design and manufacturing of an optical system or the correct focus of a camera. MTF also gives out essential information on which defaults or aberrations appear on an optical objective, and so enables to diagnose potential design or manufacturing issues on a production line or R&D prototype. Test benches and algorithms have been defined and developed in order to satisfy the growing needs in optical objectives qualification as the latter become more and more critical in their accuracy and quality specification. Many methods are used to evaluate the Modulating Transfer Function. Slit imaging and scanning on a camera, MTF evaluation thanks to wavefront measurement or imaging fixed slanted knife edge on the detector of the camera. All these methods have pros and cons, some lack in resolution, accuracy or don’t enable to compare simulated MTF curves with real measured data. These methods are firstly reminded in this paper. HGH has recently developed an improved and mixed version of a scanning technique used on a slanted knife edge giving a more accurate, ergonomic, high resolution and precise Line Spread Function (LSF) and one axis MTF measurement of a camera. A selected single pixel corresponding to a precise field point of the camera is scanned with sub pixelic resolution by the tilted knife edge thus enabling an optimized accuracy for LSF and MTF curves. The experimental protocol which requires a high-performance collimator, a scanning wheel device and a camera set up is detailed in this paper. Explained simulations are done to prove the under 1% accuracy of this method with regards to the different characteristics of the camera. All the parameters of this improved measurement technique are described and their effect criticized to give out all the result influence of these variables. These simulations and the algorithms used are then confronted to real measurements on a camera thanks to a mirror-based collimator and a scanning wheel device equipped with a slanted knife edge target.
This paper discusses a new capability developed for and results from a field portable test set for Gen 2 and Gen 3 Image Intensifier (I2) tube-based Night Vision Goggles (NVG). A previous paper described the test set and the automated and semi-automated tests supported for NVGs including a Knife Edge MTF test to replace the operator's interpretation of the USAF 1951 resolution chart. The major improvement and innovation detailed in this paper is the use of image analysis algorithms to automate the characterization of spot defects of I² tubes with the same test set hardware previously presented. The original and still common Spot Defect Test requires the operator to look through the NVGs at target of concentric rings; compare the size of the defects to a chart and manually enter the results into a table based on the size and location of each defect; this is tedious and subjective. The prior semi-automated improvement captures and displays an image of the defects and the rings; allowing the operator determine the defects with less eyestrain; while electronically storing the image and the resulting table. The advanced Automated Spot Defect Test utilizes machine vision algorithms to determine the size and location of the defects, generates the result table automatically and then records the image and the results in a computer-generated report easily usable for verification. This is inherently a more repeatable process that ensures consistent spot detection independent of the operator. Results of across several NVGs will be presented.
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