2004
DOI: 10.1117/12.555924
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Automated registration of hyperspectral images

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Cited by 2 publications
(3 citation statements)
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“…Images were corrected for lens and filter vignetting and non-uniformities by imaging a 99% Spectralon (Labsphere, Inc., North Sutton, NH) panel near the overflight times (similar solar zenith and azimuth) on the day after each flight under clear sky conditions and then dividing the acquired images by this reference imagery. The images were then co-registered using a phase correlation technique 18 .…”
Section: Hyperspectral Imagery Acquisition and Calibrationmentioning
confidence: 99%
“…Images were corrected for lens and filter vignetting and non-uniformities by imaging a 99% Spectralon (Labsphere, Inc., North Sutton, NH) panel near the overflight times (similar solar zenith and azimuth) on the day after each flight under clear sky conditions and then dividing the acquired images by this reference imagery. The images were then co-registered using a phase correlation technique 18 .…”
Section: Hyperspectral Imagery Acquisition and Calibrationmentioning
confidence: 99%
“…In this subproblem, we need to estimate L i from the low-rank tensor Z i . By ignoring the variables irrelevant to L i in (7), we can get the subproblem:…”
Section: ) Low-rank Tensor Regularization Termmentioning
confidence: 99%
“…T HANKS to the advancements in imaging technology, hyperspectral image (HSI) is capable of providing abundant information regarding the wavelengths beyond the visible spectrum and have a wide range of applications including medical diagnosis [1], [2], [3], geothermal exploration [4], [5], [6], agriculture [7], [8], [9]. Unfortunately, different types of noise including stripes, deadlines, impulse noise, and Gaussian noise will be inevitably introduced in the hyperspectral imaging process, which considerably damages the image quality and limits further applications including image classification [10], [11] and target detection [12], [13].…”
Section: Introductionmentioning
confidence: 99%