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Optical Engineering • Open Access

Resampling in hyperspectral cameras as an alternative to correcting keystone in hardware, with focus on benefits for optical design and data quality
Author(s): Andrei Fridman; Gudrun Høye; Trond Løke

Paper Abstract

Current high-resolution hyperspectral cameras attempt to correct misregistration errors in hardware. This severely limits other specifications of the hyperspectral camera, such as spatial resolution and light gathering capacity. If resampling is used to correct keystone in software instead of in hardware, then these stringent requirements could be lifted. Preliminary designs show that a resampling camera should be able to resolve at least 3000–5000 pixels, while at the same time collecting up to four times more light than the majority of current high spatial resolution cameras. A virtual camera software, specifically developed for this purpose, was used to compare the performance of resampling and hardware corrected cameras. Different criteria are suggested for quantifying the camera performance. The simulations showed that the performance of a resampling camera is comparable to that of a hardware corrected camera with 0.1 pixel residual keystone, and that the use of a more advanced resampling method than the commonly used linear interpolation, such as high-resolution cubic splines, is highly beneficial for the data quality of the resampled image. Our findings suggest that if high-resolution sensors are available, it would be better to use resampling instead of trying to correct keystone in hardware.

Paper Details

Date Published: 7 May 2014
PDF: 16 pages
Opt. Eng. 53(5) 053107 doi: 10.1117/1.OE.53.5.053107
Published in: Optical Engineering Volume 53, Issue 5
Show Author Affiliations
Andrei Fridman, Norsk Elektro Optikk AS (Norway)
Gudrun Høye, Norsk Elektro Optikk AS (Norway)
Trond Løke, Norsk Elektro Optikk AS (Norway)


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