&lt;title&gt;Array nonuniformity correction: new procedures designed for difficult measurement conditions&lt;/title&gt;

Sieglinger, Breck A.; Norman, James D.; Meshell, William M.; Flynn, David S.; Thompson, Rhoe A.; Goldsmith, George C.

doi:10.1117/12.488620

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…The array transfer functions are highly non-linear (see and require the application of complex nonuniformity correction (NUC) techniques. Correspondingly, a significant portion of this paper will be dedicated to the explanation of the MIT LL NUC process, which is a novel twist on the industry standard sparse grid calibration technique developed by the Kinetic Hardware in the Loop Simulator (KHILS) laboratory at Eglin Air Force Base, Florida [1]. The MIT LL NUC procedure can repeatedly correct NODDS arrays to less than 1% residual nonuniformity 1 over the drive ranges of interest (see .…”

Section: Introductionmentioning

confidence: 99%

Characterization and comparison of 128x128 element nuclear optical dynamic display system resistive arrays

et al. 2006

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Dynamic infrared scene projection is a common technology used to provide end to end testing and characterization of infrared sensor systems. Scene projection technology will play an increasing role in infrared system evaluation and development as the cost and risk of flight testing increases and new display technologies begin to emerge. This paper describes a series of tests performed in the Seeker Experimental System (SES) at MIT Lincoln Laboratory (MIT LL). A small collection of 128×128 element Nuclear Optical Dynamic Display System (NODDS) resistive arrays were tested and compared using FIESTA drive electronics developed by ATK Mission Research. The residual spatial nonuniformity of the NODDS arrays were calculated after applying a sparse grid based nonuniformity correction algorithm developed at MIT LL. The nonuniformity correction algorithm is a slightly modified version of the industry standard sparse grid technique and is outlined in this paper. Additional metrics used to compare the arrays include emitter temporal response, raw nonuniformity, transfer function smoothness, dynamic range, and bad display pixel characteristics.

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Section: Introductionmentioning

confidence: 99%

Characterization and comparison of 128x128 element nuclear optical dynamic display system resistive arrays

et al. 2006

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“…Many approaches have been developed to correct emitter array non-uniformity [1][2][3][4][5][6][7]. These generally employ three basic steps: data collection, curve fitting, and generation of NUC coefficients.…”

Section: Introductionmentioning

confidence: 99%

Advances in iterative non-uniformity correction techniques for infrared scene projection

et al. 2015

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Santa Barbara Infrared (SBIR) is continually developing improved methods for non-uniformity correction (NUC) of its Infrared Scene Projectors (IRSPs) as part of its comprehensive efforts to achieve the best possible projector performance. The most recent step forward, Advanced Iterative NUC (AI-NUC), improves upon previous NUC approaches in several ways. The key to NUC performance is achieving the most accurate possible input drive-toradiance output mapping for each emitter pixel. This requires many highly-accurate radiance measurements of emitter output, as well as sophisticated manipulation of the resulting data set. AI-NUC expands the available radiance data set to include all measurements made of emitter output at any point. In addition, it allows the user to efficiently manage that data for use in the construction of a new NUC table that is generated from an improved fit of the emitter response curve. Not only does this improve the overall NUC by offering more statistics for interpolation than previous approaches, it also simplifies the removal of erroneous data from the set so that it does not propagate into the correction tables. AI-NUC is implemented by SBIR's IRWindows4 automated test software as part its advanced turnkey IRSP product (the Calibration Radiometry System or CRS), which incorporates all necessary measurement, calibration and NUC table generation capabilities. By employing AI-NUC on the CRS, SBIR has demonstrated the best uniformity results on resistive emitter arrays to date.

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“…The NUC procedure used in this paper is commonly referred to as a sparse grid measurement [2,3] . In this method, a grid of emitter pixels is displayed, spaced far enough apart such that neighboring projected ON pixels are not interacting in the camera.…”

Section: Sparse Grid Radiancementioning

confidence: 99%

LWIR NUC using an uncooled microbolometer camera

et al. 2010

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Performing a good non-uniformity correction is a key part of achieving optimal performance from an infrared scene projector. Ideally, NUC will be performed in the same band in which the scene projector will be used. Cooled, large format MWIR cameras are readily available and have been successfully used to perform NUC, however, cooled large format LWIR cameras are not as common and are prohibitively expensive. Large format uncooled cameras are far more available and affordable, but present a range of challenges in practical use for performing NUC on an IRSP. Santa Barbara Infrared, Inc. reports progress on a continuing development program to use a microbolometer camera to perform LWIR NUC on an IRSP. Camera instability and temporal response and thermal resolution are the main difficulties. A discussion of processes developed to mitigate these issues follows.

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<title>Array nonuniformity correction: new procedures designed for difficult measurement conditions</title>

Cited by 9 publications

References 9 publications

Characterization and comparison of 128x128 element nuclear optical dynamic display system resistive arrays

Characterization and comparison of 128x128 element nuclear optical dynamic display system resistive arrays

Advances in iterative non-uniformity correction techniques for infrared scene projection

LWIR NUC using an uncooled microbolometer camera

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