Hyperspectral images of
natural scenes 2004
The eight hyperspectral
here were acquired from the same sites as those illustrated in Figure 1
Nascimento, and Amano, 2004,
and are a representative sample of the 25 images used
in that study. They consisted
mixture of rural scenes from the Minho
Portugal, containing, rocks,
trees, leaves, grass, and earth and urban scenes from the cities of
Porto and Braga, Portugal. Images were obtained during the
2002 and 2003, almost always under a clear sky. Particular care was
taken to avoid scenes containing movement. Scenes were
illuminated by direct sunlight in clear or
almost clear sky. Colour pictures of the eight representative
are shown here, and full-size
versions (each about 4MB) can be downloaded by clicking on each.
(effective spectral reflectances) at each pixel in each of these
can be downloaded as a WinZip file by clicking on the link at
the bottom of each picture. Each zipped file
contains contains for each
scene-reflectances file (size e.g. 1018 x 1339 x 33), a Matlab
radiance-by-reflectances file for converting reflectances to radiances
(33 x 2), a Matlab reflectances file for the Munsell surface in the
scene (33 x 2), a bright BMP image of the scene, and a Microsoft RTF
information file. The version of Matlab used to save
these files was 188.8.131.52 (R2006a). Details of the
hyperspectral system, image acquisition, and
processing are given further down the page.
If you use these images, please cite this source publication: Foster, D.H., Amano, K., Nascimento, S.M.C., & Foster, M.J. (2006). Frequency of metamerism in natural scenes. Journal of the Optical Society of America A, 23, 2359-2372.
Time-lapse hyperspectral radiance images, taken at intervals across the day, are available here
Details of hyperspectral system, image acquisition, and processing
The present system used a low-noise Peltier-cooled digital camera providing an x-y spatial resolution of 1344 x 1024 pixels (Hamamatsu, model C4742-95-12ER, Hamamatsu Photonics K. K., Japan) with a fast tunable liquid-crystal filter (VariSpec, model VS-VIS2-10-HC-35-SQ, Cambridge Research & Instrumentation, Inc., MA) mounted in front of the lens, together with an infrared blocking filter. Focal length was typically set to 75 mm and aperture to f/16 or f/22 to achieve a large depth of focus. The line-spread function of the system was close to Gaussian with standard deviation approx. 1.3 pixels at 550 nm. The intensity response at each pixel, recorded with 12-bit precision, was linear over the entire dynamic range. The peak-transmission wavelength was varied in 10-nm steps over 400–720 nm and the bandwidth (FWHM) was 10 nm at 550 nm, decreasing to 7 nm at 400 nm and increasing to 16 nm at 720 nm. The acceptance angle of the camera was approx. 6 deg of visual angle.
Before image acquisition, the exposure at each wavelength was determined by an automatic routine so that maximum pixel output was within 86–90% of saturation. Immediately after acquisition, the reflected spectrum from a small flat grey (Munsell N5 or N7) reference surface in the scene was recorded with a telespectroradiometer (SpectraColorimeter, PR-650, Photo Research Inc., Chatsworth, CA), the calibration of which was traceable to the National Physical Laboratory.
The raw images acquired
hyperspectral camera were corrected only for dark noise, spatial
nonuniformities (mainly off-axis vignetting), stray light, and any
wavelength-dependent variations in magnification or
For all scenes, the signal at 400 nm was relatively noisy, but data for
this wavelength were not excluded. For Scene 5, however, the
signal at 720 nm was excessively noisy, and data for this
wavelength were excluded, so the
size of the scene-reflectances file is 1020 × 1339
32 (in any event, the signals at 400 and 720 nm make relatively small
to the in-vivo response of human cones to natural reflected
(labelled "_lax") have
also been included for Scenes 1, 2, 3, and 5. These edited
have been corrected for some nonlinear chromatic artefacts arising from
movement of foliage within the scene during image
reflectances at each
pixel were estimated by
normalizing the corrected signal against that obtained from the grey
reference surface in the scene. An informal
description of effective spectral
reflectances and the effective global illuminant are given below. Further technical
given in Foster
the latter including additional calibration data (p.
2360) and an
effective spectral reflectances with direct and indirect illumination (Appendix
These data are for personal use only. Acknowledgement of the relevant source publications should be given in any published work arising from these data: Foster, D.H., Amano, K., Nascimento, S.M.C., & Foster, M.J. (2006). Frequency of metamerism in natural scenes. Journal of the Optical Society of America A, 23, 2359-2372.
Notes on effective
and effective global illuminant
The effective spectral reflectance at each pixel was obtained by dividing the spectral radiance recorded by the hyperspectral camera at that position and wavelength by the spectral radiance recorded from a calibrated neutral reference surface (a Munsell grey) in the scene and then multiplying by the known spectral reflectance of the reference surface. The reference surface was usually flat and placed vertically facing the camera. Because surfaces oriented at an angle to the camera may reflect more light than vertical surfaces, their effective spectral reflectances may exceed unity.
There are three ways to
deal with this.
1. If there is a Munsell
grey sphere in
with a visible highlight, then multiply (wavelength-by-wavelength) the
effective spectral reflectance at each
pixel by the effective spectral reflectance
at the flat reference and then divide by the effective spectral reflectance
at the highlight. If there is a true specular highlight in the scene,
e.g. from water (Scene 4, top right-hand corner), then this might
instead be used as the divisor
or it can be removed altogether from
2. Divide all the
reflectances in the scene by a constant equal to the maximum effective
spectral reflectance evaluated over all pixels and wavelengths.
3. Ignore it. The
reflectances are normally used to calculate a reflected spectrum.
Multiplying the effective spectral reflectance by the data in the
radiance-by-reflectances file recovers the original spectral radiance
recorded by the camera. Multiplying instead by a new different
illuminant spectrum will simulate the effect of replacing the original
illuminant by this new illuminant. Thus there is a trade-off between
decreasing all the spectral reflectances in the scene by a constant
factor, as in method 2, and increasing the illuminant spectrum by the
The spectrum of the effective global illuminant was obtained by taking the actual reflected spectrum from a calibrated neutral reference surface (a Munsell grey) in the scene recorded with a telespectroradiometer and dividing by the known spectral reflectance of that surface. The spectral radiance recorded by the hyperspectral camera at each position may then interpreted as a product of this effective global illuminant and the effective spectral reflectance at that position.
Further technical details are given in Foster et al. (2006), particularly Appendix A, pp. 2370-2371.
Tutorial on transforming hyperspectral images
Click here for a tutorial on transforming hyperspectral image reflectances into reflected radiances and RGB colour images.
The tutorial includes sample code (MATLAB, The MathWorks Inc) and technical notes on the interpretation of reflectance spectra from natural scenes. Also available for download is a zipped package containing a small test hyperspectral image, daylight illuminant spectra, and a conversion routine for producing sRGB images.
(c) D. H. Foster, S. M. C. Nascimento, and K. Amano, February 2012
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