OSA's Digital Library

Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 20, Iss. 28 — Dec. 31, 2012
  • pp: 29413–29425
« Show journal navigation

Reflectances from a supercontinuum laser-based instrument: hyperspectral, polarimetric and angular measurements

Romain Ceolato, Nicolas Riviere, and Laurent Hespel  »View Author Affiliations


Optics Express, Vol. 20, Issue 28, pp. 29413-29425 (2012)
http://dx.doi.org/10.1364/OE.20.029413


View Full Text Article

Acrobat PDF (5793 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Recent developments of active hyperspectral systems require optical characterization of man-made materials for instrument calibration. This work presents an original supercontinuum laser-based instrument designed by Onera, The French Aerospace Lab, for fast hyperspectral polarimetric and angular reflectances measurements. The spectral range is from 480 nm to 1000 nm with a 1 nm spectral resolution. Different polarization configurations are made possible in whole spectrum. This paper reviews the design and the calibration of the instrument. Hyper-spectral polarimetric and angular reflectances are measured for reference and man-made materials such as paint coatings. Physical properties of reflectances as positivity, energy conservation and Helmholtz reciprocity are retrieved from measurements.

© 2012 OSA

1. Introduction

Hyperspectral sensors have been used intensively for years in the remote-sensing community [1

1. G. Shaw and H. K. Burke, “Spectral imaging for remote sensing,” Lincoln Laboratory Journal 14, 3–28 (2003).

3

3. E. Ientilucci and M. Gartley, “Impact of BRDF on physics-based modeling as applied to target detection in hyperspectral imagery,” Proc. SPIE 7334, 73340T1 (2009).

]. Developments [4

4. R. R. Alfano and S. L. Shapiro, “Emission in the region 4000 to 7000 A via four-photon coupling in glass,” Phys. Rev. Lett. 24, 584–587 (1970). [CrossRef]

] in nanostructured fiber optics and compact pulsed lasers have resulted in the conception of supercontinuum laser sources. These sources are generated using a pulsed laser propagating through a non-linear medium. It results in a spectral broadening [5

5. J. Dudley, G. Genty, and S. Coen, “Supercontinuum generation in photonic crystal fiber,” Rev. Mod. Phys. 78, 1135–1184 (2006). [CrossRef]

] and the creation of white directional coherent light. The combination of supercontinuum laser sources with hyperspectral sensors are of rising interest for civilian [6

6. Y. Peng and R. Lu, “Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content,” Postharvest Biol. Tec. 48, 52–62 (2008). [CrossRef]

8

8. F. Larusson, S. Fantini, and E. Miller, “Hyperspectral image reconstruction for diffuse optical tomography,” Biomed. Opt. Express 2, 946–965 (2011). [CrossRef] [PubMed]

] and defense [9

9. B. Johnson, R. Joseph, M. Nischan, A. Newbury, J. Kerekes, H. Barclay, B. Willard, and J. Zayhowski, “A compact, active hyperspectral imaging system for the detection of concealed targets,” Proc. SPIE 3710, 144–157 (1999). [CrossRef]

11

11. T. Hakala, J. Suomalainen, S. Kaasalainen, and Y. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express 20, 7119–7127 (2012). [CrossRef] [PubMed]

] applications.

Active hyperspectral systems, such as active hyperspectral imaging [12

12. M. L. Nischan, R. M. Joseph, J. C. Libby, and J. P. Kerekes, “Active spectral Imaging,” Lincoln Laboratory Journal 14, 131–144 (2003).

] or hyperspectral Light Detection And Ranging (LiDAR) [13

13. Y. Chen, E. Raikkonen, S. Kaasalainen, J. Suomalainen, T. Hakala, J. Hyyppa, and R. Chen, “Two-channel Hyperspectral LiDAR with a Supercontinuum laser source,” Sensors 10, 7057–7066 (2010). [CrossRef] [PubMed]

], are based on these recent advances. These systems are used in rural and urban environments where natural materials (eg. agricultural fields or canopies) but also man-made materials (eg. ceramics, composites, metallic and plastic compounds or paint coatings) are involved. These latter materials are particularly known to scatter light not uniformly in space as they exhibit severe anisotropy reflection [14

14. B. Mc Guckin, D. Haner, and R. Menzies, “Multiangle imaging spectroradiometer: optical characterization of the calibration panels,” J. Quant. Spectros. Radiat. Transfer. 15, 281–290 (2007).

].

Current hyperspectral sensors present a high spectral resolution but often a low spatial resolution [15

15. M. Eismann and R. Hardie, “Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 43, 455–465 (2005). [CrossRef]

, 16

16. J. Bieniarz, D. Cerra, J. Avbelj, and P. Reinartz, “Resolution enhancement of hyperspectral imagery through spatial-spectral data fusion,” in Proceedings of ISPRS Hannover Workshop 2011: High-Resolution Earth Imaging for Geospatial Information 33–37 (2011).

]. However, sensors technology is improving fast enough (e.g lower signal-to-noise ratio and refresh rate) to use low beam divergence laser sources for active systems with low footprint size. As a consequence, the illuminated target surface decreases and a strong reflectance anisotropy is to be measured for man-made materials. Lambertian approximation may fail for such applications and accurate materials reflectances are needed.

Man-made materials have distinctive spectral, polarimetric and angular reflectances resulting from complex light scattering and absorption phenomema (i.e. surface or subsurface scattering [17

17. K. Ellis, “Polarimetric bidirectional reflectance distribution function of glossy coatings,” J. Opt. Soc. Am. A 13, 1758–1762 (1996). [CrossRef]

]). Dedicated instruments [18

18. S. Nevas, F. Manoocheri, and E. Ikonen, “Gonioreflectometer for measuring spectral diffuse reflectance,” Appl. Opt. 43, 6391–6399 (2004). [CrossRef] [PubMed]

20

20. H. Li, S. C. Foo, K. E. Torrance, and S. H. Westin, “Automated three-axis gonioreflectometer for computer graphics applications,” Opt. Eng. 45, 043605 (2005). [CrossRef]

] are used to evaluate at discrete wavelengths Bidirectional Reflectance Factor (BRF) or Bidirectional Reflectance Distribution Function (BRDF) but also Directional Hemispherical Reflectance (DHR). However, more accurate and comprehensive optical characterization (i.e. full spectral range, polarimetric and high angular resolution) is useful for new applications.

In this paper, we report an original and fast supercontinuum laser-based instrument to measure the hyperspectral, polarimetric and angular reflectances of materials with a high angular resolution. First, we introduce a tensorial framework derived from hyperspectral remote-sensing to describe the light scattered by a sample for a continuous spectrum. Our instrument is described and its calibration procedure is detailed. Then, hyperspectral polarimetric and angular reflectance measurements are carried out on reference materials and paint coatings with various optical characteristics. Man-made materials characterization is split in two parts. On the one hand, known optical properties of reference materials are retrieved and compared to identify measurement errors. On the other hand, we measure optical properties from unknown materials and discuss the results on limited domains. Lastly, results are checked to respect physical principles such as the energy conservation or the Helmholtz reciprocity.

2. Theory

In this section, the basic radiometric quantities adapted to hyperspectral polarimetric and angular reflectances are outlined.

Spectral radiometry is the science of measuring the spectral intensity of electromagnetic field vectors while polarimetry analyze the polarization state of an electromagnetic field. The terminology in this paper uses the definitions accepted by the International Standards Organizations (ISO) and the International Commission on Illumination (CIE). Morevover, the huge amount of data involved in hyperspectral measurements implies the use of tensorial quantities [21

21. R. Ceolato, N. Riviere, L. Hespel, and B. Biscans, “Probing optical properties of nanomaterials,” SPIE Newsroom (January12, 2012). doi: [CrossRef] .

]. Notations of the hyperspectral tensors are listed in Table 1.

Table 1. Notations used in the hyperspectral polarimetric tensorial framework where m and n refer to the incident and reflected polarization states.

table-icon
View This Table
| View All Tables

Hyperspectral measurements have been carried out in many scientific fields. For instance, hyperspectral remote-sensing data are stored in hypercubes [22

22. N. Renard and S. Bourennane, “Improvement of target detection methods by multiway filtering,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 46, 2407–2417 (2008). [CrossRef]

] that contains both spatial and spectral information. We extend this method to store hyperspectral polarimetric and angular information. Figure 1 illustrates the geometry used in the framework in a spherical coordinate system.

Fig. 1 Definition of the hyperspectral tensors in a spherical coordinate system.

Let’s define a 5-order hyperspectral tensor ℋ(i1, i2; r1, r2; l) ∈ ℝI1×I2×R1×R2×L where i1, i2 go from 0 to I1, I2 referring to numbers of angles of incidence, r1, r2 go from 0 to R1, R2 referring to numbers of reflected angles and l goes from 0 to L referring to the number of wavelengths. Basic tensors needed are the polarized irradiance tensor ℰm(i1, i2; r1, r2; l) and the polarized radiance tensor rn(i1,i2;r1,r2;l). The scripts m and n refer respectively to the incident and reflected polarization states. The term cosθ(r1) · ΔA is used in the definitions of tensors and corresponds to the projected area varying with the observation angle and ΔΩ to the solid angle. It is called the cosine law or the Lambert law. These tensors can be retrieved from the power tensors 𝒫(i1, i2; r1, r2; l) directly measured from our instrument, i.e.,
m(i1,i2;r1,r2;l)=𝒫im(i1,i2;r1,r2;l)cosθ(r1)A
(1)
rn(i1,i2;r1,r2;l)=𝒫rn(i1,i2;r1,r2;l)cosθ(r1)AΩ
(2)

Let’s define the polarimetric bidirectional reflectance distribution function tensor as the ratio of the polarized reflected radiance tensor to the polarized incident irradiance tensor. It corresponds to the tensorial representation of the spectral polarimetric BRDF or BRF defined by Nicodemus [23

23. F. Nicodemus, “Directional reflectance and emissivity of an opaque surface,” Appl. Opt. 4, 767–773 (1965). [CrossRef]

] i.e.,
BRDFmn(i1,i2;r1,r2;l)=rn(i1,i2;r1,r2;l)m(i1,i2;r1,r2;l)
(3)

For reflectance measurements, BRF is used as exposed by G. Schaepman-Strub et al. [26

26. G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing - definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006). [CrossRef]

]. Also, the BRDF can be computed from the BRF using a simple proportional relation for small solid angles and directional light sources [24

24. J. V. Martonchik, C. J. Bruegge, and A. Strahler, “A review of reflectance nomenclature used in remote sensing,” Remote Sens. Rev. 19, 9–20 (2000). [CrossRef]

]. Material appearance is described as “diffuse” or “specular” from its BRDF which results from different scattering processes. In this paper, we report spectral polarimetric BRDF as it is found in literature [25

25. A. Ferrero, J. Campos, A. M. Rabal, A. Pons, M. L. Hernanz, and A. Corrons, “Principal components analysis on the spectral bidirectional reflectance distribution function of ceramic colour standards,” Opt. Express 19, 19199–19211 (2011). [CrossRef] [PubMed]

]. The commonly used BRDF.cosθ representation is preferred for experimental reasons.

For in-plane measurements, we define a 3-order principal-plane hyperspectral bidirectional reflectance tensor. The principal-plane (θi, ϕi = ϕ0; θr, ϕr = ϕ0) is defined by the incident laser source, the illuminated surface and the detector.
HBRDF,0mn=rn(i1,r1;l)im(i1,r1;l)
(4)

We also define the principal-plane polarimetric directional hemispherical reflectance tensor as the ratio of the principal-plane polarized reflected power tensor to the principal-plane polarized incident power tensor, i.e.,
DHR,0mn(l)=𝒫rn(l)𝒫im(l)
(5)

There are two ways to measure this quantity: either by measuring the power ratio (e.g. using an integrating sphere instrument), or by integrating the principal-plane BRDF over reflected angles under the assumption that the surface is a perfect Lambertian surface. The latter way is useful to verify to the energy conservation.

3. Instrument and technique

Onera develops a hyperspectral polarimetric reflectometer (Melopee) to measure reflectance properties of various types of materials in the visible and near infrared (VIS/NIR) from 480 nm to 1000 nm with a spectral resolution lower than 1 nm. From these measurements stored as hyperspectral tensors, one can retrieve the usual spectral polarimetric DHR, BRF or BRDF of materials. Specifications of the instrument are given in Table 2.

Table 2. Specifications of the VIS/NIR hyperspectral version of Melopee instrument.

table-icon
View This Table
| View All Tables

A multispectral version of the instrument was previously reported [27

27. N. Riviere, R. Ceolato, and L. Hespel, “Multispectral polarized BRDF: design of a highly resolved reflectometer and development of a data inversion technique,” Opt. Appl. 42, 7–22 (2012).

]. Multispectral and polarimetric measurements were carried out on paint coatings. A schematic of the hyperspectral version of instrument Melopee is presented in Fig. 2.

Fig. 2 Schematic of the VIS/NIR hyperspectral version of Melopee instrument. The incident lighting system is a supercontinuum laser coupled to wide-band polarizers. The sensing system is composed of a CCD sensor based spectrophotometer mounted on a goniometer platform.

The incident lighting system consists in a supercontinuum laser used as a coherent collimated hyperspectral unpolarized light source. The laser source is fully unpolarized at full power and is coupled to wide-band polarizers (Codixx colorPol® VISIR) to select incident polarization states. The variation of incident power is measured to ensure stable measurements. The polarizers efficiency was found higher than 98% on the whole spectral range using a VIS/NIR polarimeter. The sensing system measures the reflected power tensor 𝒫r with an angular resolution of 0.1°. It provides highly resolved measurements and is composed of a grating CCD-based spectrophotometer mounted on a goniometer platform at 1 m from the sample. The noise-equivalent BRDF was measured lower than 10−7 sr−1. A 5-axis fully automated sample holder facilitates the measurement procedure. A coarse alignment of the sample holder is done using a specular sample by measuring the specular reflection for various angles. A fine alignment is obtained by measuring the angular scattered light at various symmetric positions using a Lambertian sample. By repeating these alignment measurements, the procedure is complete when a root-mean-square error lower than 1% is obtained. All measurements are carried out in the principal-plane and are fully interfaced via GPIB and PCI cards to control step motors using homemade software.

Our measurement procedure is based on the Standard ASTM-E1392-96 [28

28. “Standard practice for angle resolved optical scatter measurements on specular or diffuse surfaces,” Am. Soc. Test Mater Standard E1392–96 (1997).

]. Hyperspectral calibration is known to be quite complex as it involves huge amount of data due to the number of spectral bands [2

2. D. Manolakis and D. Marden, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14, 79–116 (2003).

]. A proper calibration process is needed to measure BRDF,0mn and to retrieve BRDF of reflectors. Each optical component in our instrument has its own spectral, radiometric and angular signature to be taken into account. The calibration procedure is based on a relative calibration extended to hyperspectral polarimetric measurements. It requires the determination of the instrument function using a standard Lambertian reference (LabSphere Spectralon®). It is direct, fast and requires no external measurements. Verification is carried out on other reference samples in Section 4 and discussed in details in Section 5. We retrieve the main BRDF physical properties (i.e., positivity, energy conservation and Helmholtz reciprocity) to complete the validity of our calibration method.

4. Results

The need of Lambertian surfaces is crucial for imaging and non-imaging system calibration. White, grey or color Spectralon (PTFE) provided by LabSphere samples are used as references in remote sensing and active imaging for calibration. Spectralon samples are well documented [29

29. C. L. Betty, “The measured polarized bidirectional reflectance distribution function of a Spectralon calibration target,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 4, 2183–2185 (1996).

, 30

30. G. T. Georgiev and J. J. Butler, “BRDF study of gray-scale Spectralon,” Proc. SPIE 7081, 71–79 (2008).

] for monochromatic and unpolarized illumination, but very few experiments were conducted to expose the Lambertian nature of such samples with a hyperspectral polarized coherent illumination.

We report here measurements from our calibrated instrument on Spectralon Reflectance Standard (SRS), Spectralon Diffuse Color Standards (SCS) and a glossy paint coating sample to demonstrate the capabilities of our instrument. The importance of hyperspectral polarimetric and angular optical studies for man-made materials is later discussed.

4.1. Spectralon Reflectance Standards (SRS)

We carry out measurements on spectrally neutral Spectralon SRS-99 (white) and SRS-20 (dark grey) with respective DHR = 0.99 and DHR = 0.20. The illumination is P-polarized and the detection unpolarized. Figure 3 shows the measured BRDF,0mn at normal angle of incidence for these samples.

Fig. 3 BRDF,0pu measurements for Lambertian materials : Spectralon SRS-99 and SRS-20. The illumination is P-polarized and the detection unpolarized..

Table 3 presents averaged angular, radiometric, spectral and total spectrally averaged root-mean-square (RMS) errors from data provided by LabSphere [31

31. Labsphere, “A guide to diffuse reflectance coatings and materials,” http://www.prolite.co.uk/File/coatingsmaterialsdocumentation.php.

].

Table 3. RMS Errors for Spectralon SRS.

table-icon
View This Table
| View All Tables

The retrieved BRDF of SRS samples are found to behave closely as a Lambertian surface at normal angle of incidence from 480 nm to 1000 nm. The angular and radiometric RMS errors are lower than 1% whereas the spectral RMS error is close to 0% due to the spectrally independent nature of the samples. The angular RMS error is almost 10 times higher for SRS-20 sample. The total RMS error is found between 1% and 2% for SRS samples. We explain the large angular RMS error by the possible unperfect Lambertian nature of the SRS-20 sample. This explanation is supported by similar errors previously reported for SRS-20 [31

31. Labsphere, “A guide to diffuse reflectance coatings and materials,” http://www.prolite.co.uk/File/coatingsmaterialsdocumentation.php.

]. The low RMS errors (less than 2%) found for reference samples confirm the good reliability of our instrument.

4.2. Spectralon Diffuse Color Standards (SCS)

We perform similar measurements under the same experimental conditions on spectrally dependent Spectralon SCS-CY (cyan), SCS-GN (green), SCS-VI (violet) and SCS-YW (yellow). The illumination is P-polarized and the detection unpolarized. Figure 4 shows the measured BRDF,0mn at normal angle of incidence for these samples.

Fig. 4 BRDF,0pu measurements for color Lambertian materials : Spectralon SCS-CY, SCS-GN, SCS-VI and SCS-YW. The illumination is P-polarized and the detection unpolarized.

Angular, radiometric, spectral and total spectrally averaged RMS errors are computed in Table 4 from data provided by LabSphere [31

31. Labsphere, “A guide to diffuse reflectance coatings and materials,” http://www.prolite.co.uk/File/coatingsmaterialsdocumentation.php.

].

Table 4. RMS Errors for Spectralon SCS.

table-icon
View This Table
| View All Tables

As reported for Spectralon SRS, the BRDF of Spectralon SCS are found to behave closely as a Lambertian surface at normal angle of incidence from 480 nm to 1000 nm. The angular and radiometric RMS errors are close to 1% whereas the spectral RMS error is lower than 0.5%. These errors are much higher for SCS samples compared with SRS samples. The total RMS error is found close to 2.5%. We explain larger RMS errors by the unperfect Lambertian nature of the SCS samples. The colored pigments used during the manufacturing process might have altered the Lambertian nature of the sample. This deviation from a perfect ideal Lambertian surface can explain errors found in the DHR computation as explained in Section 2.

4.3. Commercial paint coatings measurements

Fig. 5 BRDF,0pu measurements for a commercial urban glossy paint coating for an incident P-polarized (left) and S-polarized illumination (right). Detection is unpolarized.

Our measurements provide an illustration of the importance of hyperspectral polarimetric and angular optical studies of man-materials for active hyperspectral systems. Results presented for this sample cannot be extended for all type of materials and specific studies must be undertaken for other materials.

5. Discussion

The reciprocity principle is verified if BRDF(θi;θf ;λ) = BRDF(θr;θi;λ) or ℋBRDF,0 (i1; r1; l) = ℋBRDF,0 (r1; i1; l) in our tensorial framework. The plot of this equation is a straight line passing through the origin. Measurements for a glossy paint coating are used to verify the reciprocity principle for the BRDF. Figure 7 plots the BRDF(θi;θr) vs BRDF(θr;θi) for different wavelengths VIS/NIR.

Fig. 6 Energy conservation for Spectralon SRS and SCS. Comparison between computed DHR from BRDF,0mn measurements (Melopee) and DHR provided by LabSphere.
Fig. 7 Helmholtz reciprocity. BRDF reciprocity validation for ten VIS/NIR wavelengths on a glossy paint coating from ℋBRDF,0 measurements. Incident P-polarized (on the left) and S-polarized (on the right) light are considered.

Minimal RMS errors (close to 0%) corresponds to small incident angles (θi < 50°) and maximal RMS errors (5.5%) for large incident angles (θi > 50°) for P and S incident polarized light. The BRDF itself is known to be reciprocal whereas its tensorial representation is found fairly reciprocal giving systematic instrument errors.

The verification of the BRDF physical properties shows the accuracy and the validity of our hyperspectral polarimetric and angular measurements.

6. Conclusion

The growing interest for hyperspectral sensors and supercontinuum laser sources brings new challenges for calibration and material optical characterization. Hyperspectral polarimetric and angular reflectances are more and more needed for the development of future active hyperspectral systems.

Onera has designed and developed an original supercontinuum laser-based instrument to measure hyperspectral polarimetric and angular reflectances. The instrument allows measurements from 480 nm to 1000 nm with a spectral resolution of 1 nm and a high angular resolution (less than 1°). Different polarization configurations are made possible. A great of advantage of the instrument is the ability to provide fast (less than 30 s) and comprehensive reflectances as BRF, BRDF or DHR. A dedicated calibration procedure was detailed and applied to Lambertian reference samples. The averaged measurement error was found lower than 2%. Reflectances of man-made materials are presented to illustrate the capacities of our instrument. Specular material such as a commercial glossy paint coating is studied to expose the instrument capabilities. Moreover, we retrieved and verified from our measurements the fundamental properties of the BRDF (positivity, energy conservation and Helmholtz reciprocity).

Measuring hyperspectral polarimetric and angular reflectances is one step in the route of future active hyperspectral systems. The evaluation of performances for these systems requires a solid knowledge of the optical properties of materials. The instrument and the measurements presented in this paper are to give the ability of a better, faster and more accurate calibration of systems in rural or urban environment.

Acknowledgments

This work was funded by the Onera, The French Aerospace Lab, and the Region Midi-Pyrenees. The authors are thankful for advices and helpful discussions with Pr. B. Biscans, B. Guillame and B. Tanguy, and for comments provided by anonymous reviewers.

References

1.

G. Shaw and H. K. Burke, “Spectral imaging for remote sensing,” Lincoln Laboratory Journal 14, 3–28 (2003).

2.

D. Manolakis and D. Marden, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14, 79–116 (2003).

3.

E. Ientilucci and M. Gartley, “Impact of BRDF on physics-based modeling as applied to target detection in hyperspectral imagery,” Proc. SPIE 7334, 73340T1 (2009).

4.

R. R. Alfano and S. L. Shapiro, “Emission in the region 4000 to 7000 A via four-photon coupling in glass,” Phys. Rev. Lett. 24, 584–587 (1970). [CrossRef]

5.

J. Dudley, G. Genty, and S. Coen, “Supercontinuum generation in photonic crystal fiber,” Rev. Mod. Phys. 78, 1135–1184 (2006). [CrossRef]

6.

Y. Peng and R. Lu, “Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content,” Postharvest Biol. Tec. 48, 52–62 (2008). [CrossRef]

7.

C. Zakian, I. Pretty, and R. Ellwood, “Near-infrared hyperspectral imaging of teeth for dental caries detection,” J. Biomed. Opt. 14, 14, 64047 (2009). [CrossRef]

8.

F. Larusson, S. Fantini, and E. Miller, “Hyperspectral image reconstruction for diffuse optical tomography,” Biomed. Opt. Express 2, 946–965 (2011). [CrossRef] [PubMed]

9.

B. Johnson, R. Joseph, M. Nischan, A. Newbury, J. Kerekes, H. Barclay, B. Willard, and J. Zayhowski, “A compact, active hyperspectral imaging system for the detection of concealed targets,” Proc. SPIE 3710, 144–157 (1999). [CrossRef]

10.

L. Farr, “Active Spectral Imaging for Target Detection,” EMRS DTC Technical Conference 4, 1–8 (2007).

11.

T. Hakala, J. Suomalainen, S. Kaasalainen, and Y. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express 20, 7119–7127 (2012). [CrossRef] [PubMed]

12.

M. L. Nischan, R. M. Joseph, J. C. Libby, and J. P. Kerekes, “Active spectral Imaging,” Lincoln Laboratory Journal 14, 131–144 (2003).

13.

Y. Chen, E. Raikkonen, S. Kaasalainen, J. Suomalainen, T. Hakala, J. Hyyppa, and R. Chen, “Two-channel Hyperspectral LiDAR with a Supercontinuum laser source,” Sensors 10, 7057–7066 (2010). [CrossRef] [PubMed]

14.

B. Mc Guckin, D. Haner, and R. Menzies, “Multiangle imaging spectroradiometer: optical characterization of the calibration panels,” J. Quant. Spectros. Radiat. Transfer. 15, 281–290 (2007).

15.

M. Eismann and R. Hardie, “Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 43, 455–465 (2005). [CrossRef]

16.

J. Bieniarz, D. Cerra, J. Avbelj, and P. Reinartz, “Resolution enhancement of hyperspectral imagery through spatial-spectral data fusion,” in Proceedings of ISPRS Hannover Workshop 2011: High-Resolution Earth Imaging for Geospatial Information 33–37 (2011).

17.

K. Ellis, “Polarimetric bidirectional reflectance distribution function of glossy coatings,” J. Opt. Soc. Am. A 13, 1758–1762 (1996). [CrossRef]

18.

S. Nevas, F. Manoocheri, and E. Ikonen, “Gonioreflectometer for measuring spectral diffuse reflectance,” Appl. Opt. 43, 6391–6399 (2004). [CrossRef] [PubMed]

19.

J. Liu, M. Noel, and J. Zwinkels, “Design and characterization of a versatile reference instrument for rapid, reproducible specular gloss measurements,” Appl. Opt. 44, 4631–4638 (2005). [CrossRef] [PubMed]

20.

H. Li, S. C. Foo, K. E. Torrance, and S. H. Westin, “Automated three-axis gonioreflectometer for computer graphics applications,” Opt. Eng. 45, 043605 (2005). [CrossRef]

21.

R. Ceolato, N. Riviere, L. Hespel, and B. Biscans, “Probing optical properties of nanomaterials,” SPIE Newsroom (January12, 2012). doi: [CrossRef] .

22.

N. Renard and S. Bourennane, “Improvement of target detection methods by multiway filtering,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 46, 2407–2417 (2008). [CrossRef]

23.

F. Nicodemus, “Directional reflectance and emissivity of an opaque surface,” Appl. Opt. 4, 767–773 (1965). [CrossRef]

24.

J. V. Martonchik, C. J. Bruegge, and A. Strahler, “A review of reflectance nomenclature used in remote sensing,” Remote Sens. Rev. 19, 9–20 (2000). [CrossRef]

25.

A. Ferrero, J. Campos, A. M. Rabal, A. Pons, M. L. Hernanz, and A. Corrons, “Principal components analysis on the spectral bidirectional reflectance distribution function of ceramic colour standards,” Opt. Express 19, 19199–19211 (2011). [CrossRef] [PubMed]

26.

G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing - definitions and case studies,” Remote Sens. Environ. 103, 27–42 (2006). [CrossRef]

27.

N. Riviere, R. Ceolato, and L. Hespel, “Multispectral polarized BRDF: design of a highly resolved reflectometer and development of a data inversion technique,” Opt. Appl. 42, 7–22 (2012).

28.

“Standard practice for angle resolved optical scatter measurements on specular or diffuse surfaces,” Am. Soc. Test Mater Standard E1392–96 (1997).

29.

C. L. Betty, “The measured polarized bidirectional reflectance distribution function of a Spectralon calibration target,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 4, 2183–2185 (1996).

30.

G. T. Georgiev and J. J. Butler, “BRDF study of gray-scale Spectralon,” Proc. SPIE 7081, 71–79 (2008).

31.

Labsphere, “A guide to diffuse reflectance coatings and materials,” http://www.prolite.co.uk/File/coatingsmaterialsdocumentation.php.

32.

H. Li and K. E. Torrance, “A practical comprehensive light reflection model,” Technical Report PCG-05-03, Cornell Univeristy (2005).

33.

F. J. J. Clarke and D. J. Parry, “Helmholtz reciprocity: Its validity and application to reflectometry,” Ltg. Res. Technol. 17, 1–11 (1985). [CrossRef]

34.

H. J. Eom, “Energy conservation and reciprocity of random rough surface scattering,” Appl. Opt. 24, 1730–1732 (1985). [CrossRef] [PubMed]

35.

J. Greffet and M. Nieto-Vesperinas, “Field theory for generalized bidirectional reflectivity: derivation of Helmholtz’s reciprocity principle and Kirchhoff’s law,” J. Opt. Soc. Am. A 15, 2735–2744 (1998). [CrossRef]

36.

H. Okayama and I. Ogura, “Experimental verification of nonreciprocal response in light scattering from rough surfaces,” Appl. Opt. 23, 3349–3352 (1984). [CrossRef] [PubMed]

37.

W. H. Venable, “Comments on reciprocity failure,” Appl. Opt. 24, 3943 (1985). [CrossRef] [PubMed]

38.

W. C. Snyder, “Reciprocity of the BRDF in measurements and models of structured surfaces,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing 36, 685–691 (1998). [CrossRef]

OCIS Codes
(010.3640) Atmospheric and oceanic optics : Lidar
(290.0290) Scattering : Scattering
(290.5820) Scattering : Scattering measurements
(290.1483) Scattering : BSDF, BRDF, and BTDF
(110.4234) Imaging systems : Multispectral and hyperspectral imaging
(220.1080) Optical design and fabrication : Active or adaptive optics

ToC Category:
Remote Sensing

History
Original Manuscript: August 28, 2012
Revised Manuscript: October 18, 2012
Manuscript Accepted: October 18, 2012
Published: December 19, 2012

Citation
Romain Ceolato, Nicolas Riviere, and Laurent Hespel, "Reflectances from a supercontinuum laser-based instrument: hyperspectral, polarimetric and angular measurements," Opt. Express 20, 29413-29425 (2012)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-20-28-29413


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. G. Shaw and H. K. Burke, “Spectral imaging for remote sensing,” Lincoln Laboratory Journal14, 3–28 (2003).
  2. D. Manolakis and D. Marden, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal14, 79–116 (2003).
  3. E. Ientilucci and M. Gartley, “Impact of BRDF on physics-based modeling as applied to target detection in hyperspectral imagery,” Proc. SPIE7334, 73340T1 (2009).
  4. R. R. Alfano and S. L. Shapiro, “Emission in the region 4000 to 7000 A via four-photon coupling in glass,” Phys. Rev. Lett.24, 584–587 (1970). [CrossRef]
  5. J. Dudley, G. Genty, and S. Coen, “Supercontinuum generation in photonic crystal fiber,” Rev. Mod. Phys.78, 1135–1184 (2006). [CrossRef]
  6. Y. Peng and R. Lu, “Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content,” Postharvest Biol. Tec.48, 52–62 (2008). [CrossRef]
  7. C. Zakian, I. Pretty, and R. Ellwood, “Near-infrared hyperspectral imaging of teeth for dental caries detection,” J. Biomed. Opt.14, 14, 64047 (2009). [CrossRef]
  8. F. Larusson, S. Fantini, and E. Miller, “Hyperspectral image reconstruction for diffuse optical tomography,” Biomed. Opt. Express2, 946–965 (2011). [CrossRef] [PubMed]
  9. B. Johnson, R. Joseph, M. Nischan, A. Newbury, J. Kerekes, H. Barclay, B. Willard, and J. Zayhowski, “A compact, active hyperspectral imaging system for the detection of concealed targets,” Proc. SPIE3710, 144–157 (1999). [CrossRef]
  10. L. Farr, “Active Spectral Imaging for Target Detection,” EMRS DTC Technical Conference4, 1–8 (2007).
  11. T. Hakala, J. Suomalainen, S. Kaasalainen, and Y. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express20, 7119–7127 (2012). [CrossRef] [PubMed]
  12. M. L. Nischan, R. M. Joseph, J. C. Libby, and J. P. Kerekes, “Active spectral Imaging,” Lincoln Laboratory Journal14, 131–144 (2003).
  13. Y. Chen, E. Raikkonen, S. Kaasalainen, J. Suomalainen, T. Hakala, J. Hyyppa, and R. Chen, “Two-channel Hyperspectral LiDAR with a Supercontinuum laser source,” Sensors10, 7057–7066 (2010). [CrossRef] [PubMed]
  14. B. Mc Guckin, D. Haner, and R. Menzies, “Multiangle imaging spectroradiometer: optical characterization of the calibration panels,” J. Quant. Spectros. Radiat. Transfer.15, 281–290 (2007).
  15. M. Eismann and R. Hardie, “Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing43, 455–465 (2005). [CrossRef]
  16. J. Bieniarz, D. Cerra, J. Avbelj, and P. Reinartz, “Resolution enhancement of hyperspectral imagery through spatial-spectral data fusion,” in Proceedings of ISPRS Hannover Workshop 2011: High-Resolution Earth Imaging for Geospatial Information33–37 (2011).
  17. K. Ellis, “Polarimetric bidirectional reflectance distribution function of glossy coatings,” J. Opt. Soc. Am. A13, 1758–1762 (1996). [CrossRef]
  18. S. Nevas, F. Manoocheri, and E. Ikonen, “Gonioreflectometer for measuring spectral diffuse reflectance,” Appl. Opt.43, 6391–6399 (2004). [CrossRef] [PubMed]
  19. J. Liu, M. Noel, and J. Zwinkels, “Design and characterization of a versatile reference instrument for rapid, reproducible specular gloss measurements,” Appl. Opt.44, 4631–4638 (2005). [CrossRef] [PubMed]
  20. H. Li, S. C. Foo, K. E. Torrance, and S. H. Westin, “Automated three-axis gonioreflectometer for computer graphics applications,” Opt. Eng.45, 043605 (2005). [CrossRef]
  21. R. Ceolato, N. Riviere, L. Hespel, and B. Biscans, “Probing optical properties of nanomaterials,” SPIE Newsroom (January12, 2012). doi: . [CrossRef]
  22. N. Renard and S. Bourennane, “Improvement of target detection methods by multiway filtering,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing46, 2407–2417 (2008). [CrossRef]
  23. F. Nicodemus, “Directional reflectance and emissivity of an opaque surface,” Appl. Opt.4, 767–773 (1965). [CrossRef]
  24. J. V. Martonchik, C. J. Bruegge, and A. Strahler, “A review of reflectance nomenclature used in remote sensing,” Remote Sens. Rev.19, 9–20 (2000). [CrossRef]
  25. A. Ferrero, J. Campos, A. M. Rabal, A. Pons, M. L. Hernanz, and A. Corrons, “Principal components analysis on the spectral bidirectional reflectance distribution function of ceramic colour standards,” Opt. Express19, 19199–19211 (2011). [CrossRef] [PubMed]
  26. G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, “Reflectance quantities in optical remote sensing - definitions and case studies,” Remote Sens. Environ.103, 27–42 (2006). [CrossRef]
  27. N. Riviere, R. Ceolato, and L. Hespel, “Multispectral polarized BRDF: design of a highly resolved reflectometer and development of a data inversion technique,” Opt. Appl.42, 7–22 (2012).
  28. “Standard practice for angle resolved optical scatter measurements on specular or diffuse surfaces,” Am. Soc. Test Mater Standard E1392–96 (1997).
  29. C. L. Betty, “The measured polarized bidirectional reflectance distribution function of a Spectralon calibration target,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing4, 2183–2185 (1996).
  30. G. T. Georgiev and J. J. Butler, “BRDF study of gray-scale Spectralon,” Proc. SPIE7081, 71–79 (2008).
  31. Labsphere, “A guide to diffuse reflectance coatings and materials,” http://www.prolite.co.uk/File/coatingsmaterialsdocumentation.php .
  32. H. Li and K. E. Torrance, “A practical comprehensive light reflection model,” Technical Report PCG-05-03, Cornell Univeristy (2005).
  33. F. J. J. Clarke and D. J. Parry, “Helmholtz reciprocity: Its validity and application to reflectometry,” Ltg. Res. Technol.17, 1–11 (1985). [CrossRef]
  34. H. J. Eom, “Energy conservation and reciprocity of random rough surface scattering,” Appl. Opt.24, 1730–1732 (1985). [CrossRef] [PubMed]
  35. J. Greffet and M. Nieto-Vesperinas, “Field theory for generalized bidirectional reflectivity: derivation of Helmholtz’s reciprocity principle and Kirchhoff’s law,” J. Opt. Soc. Am. A15, 2735–2744 (1998). [CrossRef]
  36. H. Okayama and I. Ogura, “Experimental verification of nonreciprocal response in light scattering from rough surfaces,” Appl. Opt.23, 3349–3352 (1984). [CrossRef] [PubMed]
  37. W. H. Venable, “Comments on reciprocity failure,” Appl. Opt.24, 3943 (1985). [CrossRef] [PubMed]
  38. W. C. Snyder, “Reciprocity of the BRDF in measurements and models of structured surfaces,” in Proceedings of IEEE Transactions on Geoscience and Remote Sensing36, 685–691 (1998). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited