Setup for characterising the spectral responsivity of Fabry–Pérot-interferometer-based hyperspectral cameras

Hyperspectral cameras capture the spectral power distribution of the objects in the imaged view via dozens of narrow-band spectral channels of the camera. Knowledge of the spectral responsivity of the channels is essential when interpreting the acquired hyperspectral data and assessing its reliability. The spectral responsivity of the camera channels may vary within the image area. This paper presents a measurement setup and data analysis routine for characterising the spectral responsivity of a hyperspectral camera. This method was used to characterise the spectral responsivity of a Fabry–Pérot-interferometer-based hyperspectral camera. The characterisation method implemented in this study was able to reveal several channel leaks in the measured wavelength range. In the image area there is an approximately 1.5 nm shift in the channel wavelengths, and up to 10% variation in the channel bandwidths. The expanded uncertainties (k = 2) for the measured channel bandwidths, sensitivities and wavelengths were 7.9%, 9.5% and 0.64 nm, respectively.

[1]  Heikki Saari,et al.  Unmanned aerial vehicle (UAV) operated megapixel spectral camera , 2011, Security + Defence.

[2]  L. Lucy.  An iterative technique for the rectification of observed distributions , 1974 .

[3]  Alejandro Ferrero,et al.  Low-uncertainty absolute radiometric calibration of a CCD , 2006 .

[4]  Arko Lucieer,et al.  Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing , 2012, Remote. Sens..

[5]  Heikki Saari,et al.  Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture , 2013, Remote. Sens..

[6]  E. Honkavaara,et al.  Geometric Calibration of a Hyperspectral Frame Camera , 2016 .

[7]  Sabine Chabrillat,et al.  Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution , 2002 .

[8]  Heikki Saari,et al.  Miniaturized hyperspectral imager calibration and UAV flight campaigns , 2013, Remote Sensing.

[9]  Heikki Saari,et al.  Novel miniaturized hyperspectral sensor for UAV and space applications , 2009, Remote Sensing.

[10]  Tsehaie Woldai,et al.  Multi- and hyperspectral geologic remote sensing: A review , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[11]  Peter Gege,et al.  Calibration facility for airborne imaging spectrometers , 2005 .

[12]  Pantazis Mouroulis,et al.  Spectral and spatial uniformity in pushbroom imaging spectrometers , 1999 .

[13]  D. Faller,et al.  Medical hyperspectral imaging to facilitate residual tumor identification during surgery , 2007, Cancer biology & therapy.

[14]  Pierre Gouton,et al.  Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition , 2016, Sensors.

[15]  Johannes Brauers,et al.  Methods for spectral characterization of multispectral cameras , 2011, Electronic Imaging.

[16]  Seongchong Park,et al.  Spectral responsivity calibration of the reference radiation thermometer at KRISS by using a super-continuum laser-based high-accuracy monochromatic source , 2016 .

[17]  William H. Richardson,et al.  Bayesian-Based Iterative Method of Image Restoration , 1972 .

[18]  Guolan Lu,et al.  Medical hyperspectral imaging: a review , 2014, Journal of biomedical optics.

[19]  R. Jenssen,et al.  1 THE HYMAP TM AIRBORNE HYPERSPECTRAL SENSOR : THE SYSTEM , CALIBRATION AND PERFORMANCE , 1998 .

[20]  Mustafa Teke,et al.  A short survey of hyperspectral remote sensing applications in agriculture , 2013, 2013 6th International Conference on Recent Advances in Space Technologies (RAST).