Hyperspectral optical imaging of two different species of lepidoptera
© Medina et al; licensee Springer. 2011
Received: 2 November 2010
Accepted: 4 May 2011
Published: 4 May 2011
In this article, we report a hyperspectral optical imaging application for measurement of the reflectance spectra of photonic structures that produce structural colors with high spatial resolution. The measurement of the spectral reflectance function is exemplified in the butterfly wings of two different species of Lepidoptera: the blue iridescence reflected by the nymphalid Morpho didius and the green iridescence of the papilionid Papilio palinurus. Color coordinates from reflectance spectra were calculated taking into account human spectral sensitivity. For each butterfly wing, the observed color is described by a characteristic color map in the chromaticity diagram and spreads over a limited volume in the color space. The results suggest that variability in the reflectance spectra is correlated with different random arrangements in the spatial distribution of the scales that cover the wing membranes. Hyperspectral optical imaging opens new ways for the non-invasive study and classification of different forms of irregularity in structural colors.
Many insects and birds contain photonic structures self-assembled at the nanometer scale, some of which produce structural colors. Structural colors are the result of the manipulation of the flow of light due to coherent scattering associated with the presence of various forms of photonic crystal . Their reflectance spectra depend markedly on both the illumination and the viewing angle providing special visual effects such as iridescence and the basis to develop novel photonic applications and nanomaterials . In comparison with colored materials composed of absorbing dyes and pigments, structural colors usually contain periodic nanostructures embedded in the irregularity of the microstructure. Irregularity-based structures play a fundamental role in non-iridescent coloration and in surface color appearance . Their study demands new optical methods that can combine spectral variability together with detailed spatial properties. For this purpose, reflectance spectra recorded using spectrophotometer-based systems are not adequate because they may average over large diameter spots [2, 3]. Hyperspectral imaging is a common spectroscopy technique in non-invasive sensing analysis. From a stack of images taken at a series of narrow-bandwidth wavelengths, hyperspectral imaging provides a three-dimensional array or "image cube," with two spatial dimensions and the third the spectral axis [4, 5]. In comparison with multispectral methods, in hyperspectral imaging the distance between adjacent wavelengths is less than the spectral bandwidth providing the continuous spectral reflectance function pixel by pixel.
The aim of this study was to measure the reflectance spectra of different structurally colored butterfly wings using hyperspectral imaging. Previous studies on multispectral imaging have analyzed the colorimetric properties of synthetic interference coatings . Therefore, it is not clear whether hyperspectral optical imaging is adequate for reflectance estimation and the research on the irregularity of structurally colored systems. A specific aim of this investigation was the conversion of the estimated reflectance spectra of butterfly wings into perceived colors, taking into account the standard methods of colorimetry . Numerical studies have shown that colorimetric methods are useful for better understanding of the spatial distribution of micron and sub-micron structures in butterfly wings .
Two mirrors projected the light over the sample and provided the fine adjustment of the illumination angle. To acquire hyperspectral images, a monochrome charge-coupled device (CCD) camera (Hamamatsu ORCA C4742-95-12ER) was mounted normal to the sample so the specular component was excluded. The CCD camera had a spatial resolution of 1344 × 1024 pixels. Special modes of pixel combination (binning) were excluded. The camera also had an electronic shutter with a timer controlled by an external signal. A conventional objective was placed in the CCD camera. The images were acquired with a frame grabber (Matrox Meteor II digital PCI frame grabber). The frame grabber also provided the external signal to control the time shutter of the CCD camera. Setup, synchronization, and control of the frame grabber, the filter and the CCD camera were done using specific software in a PC. The illumination angle was fixed at 45° from surface normal, and the detection angle was at the normal. This is standard for measuring conditions in most commercial spectrophotometers (Commission Internationale de l'Éclairage, International Commission on Illumination CIE geometry 45°/0°). The entire hyperspectral system except the illumination source was shielded with dark opaque material and maintained in a dark room.
The calibration procedure and methods have been fully tested in hyperspectral data collection from natural scenes . The brightly colored side of each butterfly wing sample was mounted vertically in a panel containing a black hole of 3- or 1-cm diameter. The hole ensured a proper black background within the field of view of the scene. Hyperspectral data were calibrated using a white and a black reference image. The white reference image was obtained from a white diffuser (Edmund Optics opal diffuser 50 mm). The white diffuser minimized the effect of non-homogeneous spatial distribution of intensity in the white reference image. This issue will be analyzed later. The white diffuser was not a perfect diffuser and, therefore, its reflectance factor was calibrated against BaSO4 using a spectrophotometer with integrating sphere (Shimadzu UV-310-PC). The black reference image provided an estimation of the dark current noise of the CCD camera and was obtained in the dark room with the sample holder empty, with the same exposure times as in the white reference image and with the light source off. The reflectance factor  was therefore calculated using the standard two-point correction [4, 5]. The wavelength range between 400 and 718 nm was sampled at 6-nm intervals. Each hyperspectral set consisted of 54 images. The wings of two butterfly species were examined: Morpho didius (Nymphalidae) and Papilio palinurus (Papilionidae) [1, 9, 10]. The colorimetric methods employed in this study are standard for the representation of structural colors and are available elsewhere [2, 7].
Results and discussion
Fluctuations in the reflectance spectra come in part from the lack of spatial uniformity in the distribution of the scales in the wings as well as from the reflectance calibration. In the latter, the non-homogeneous spatial distribution of intensity in the white reference image was evaluated taking an additional white and black hyperspectral images. The reflectance factor of the white diffuser was therefore calculated following the same procedure as in the butterfly wings. It was found that variability in the reflectance spectra of the white diffuser at different pixel positions reaches a maximum reflectance factor of 23% at approximately 502 nm, then decreases, and increases again at longer wavelengths to reach a value of 21% at 718 nm. Since the reflectance factor of the P. palinurus was often below 10% between 620 and 718 nm, it exhibits some noise-related artifacts (see examples in Figure 2b).
International Commission on Illumination
liquid crystal tunable filter
This study was supported by the European Regional Development Fund (ERDF) through Programa Operacional Factores de Competitividade (COMPETE; FCOMP-01-0124-FEDER-014588), by the National Portuguese funds through the Fundação para a Ciência e Tecnologia (FCT; PTDC/CTM-MET/113352/2009), and by the Centre of Physics, University of Minho, Portugal. PV acknowledges the support of AFOSR grant FA9550-10-1-0020.
- Kinoshita S, Yoshioka S, Miyazaki J: Physics of structural colors. Rep Prog Phys 2008, 71: 30.View ArticleGoogle Scholar
- Wyszecki G, Stiles WS: Color Science. 2nd edition. New York: John Wiley & Sons; 1982.Google Scholar
- Vukusic P, Stavenga DG: Physical methods for investigating structural colours in biological systems. J R Soc Interface 2009, 6: S133-S148.View ArticleGoogle Scholar
- Gat N: Imaging spectroscopy using tunable filters: A review. Proc SPIE 2000, 4056: 50–64.View ArticleGoogle Scholar
- Hardeberg JY, Schmitt F, Brettel H: Multispectral color image capture using a liquid crystal tunable filter. Opt Eng 2002, 41: 2532–2548. 10.1117/1.1503346View ArticleGoogle Scholar
- Kim DB, Seo MK, Kim KY, Lee KH: Acquisition and representation of pearlescent paints using an image-based goniospectrophotometer. Opt Eng 2010, 49: 13.Google Scholar
- Gralak B, Tayeb G, Enoch S: Morpho butterflies wings color modeled with lamellar grating theory. Opt Express 2001, 9: 567–578. 10.1364/OE.9.000567View ArticleGoogle Scholar
- Foster DH, Amano K, Nascimento SMC, Foster MJ: Frequency of metamerism in natural scenes. J Opt Soc Am A 2006, 23: 2359–2372. 10.1364/JOSAA.23.002359View ArticleGoogle Scholar
- Vukusic P, Sambles R, Lawrence C, Wakely G: Sculpted-multilayer optical effects in two species of Papilio butterfly. Appl Opt 2001, 40: 1116–1125. 10.1364/AO.40.001116View ArticleGoogle Scholar
- Vukusic P, Sambles JR, Lawrence CR, Wootton RJ: Quantified interference and difraction in single Morpho butterfly scales. Proc R Soc Lond Ser B Biol Sci 1999, 266: 1403–1411. 10.1098/rspb.1999.0794View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.