Abstract

Increasing the number of imaging channels beyond the conventional three has been shown to be beneficial for a wide range of applications. However, it is mostly limited to imaging in a controlled environment, where the capture environment (illuminant) is known a priori. We propose here a novel system and methodology for multispectral imaging in an uncontrolled environment. Two images of a scene, a normal RGB and a filtered RGB are captured. The illuminant under which an image is captured is estimated using a chromagenic based algorithm, and the multispectral system is calibrated automatically using the estimated illuminant. A 6-band multispectral image of a scene is obtained from the two RGB images. The spectral reflectances of the scene are then estimated using an appropriate spectral estimation method. The proposed concept and methodology is generic one, as it is valid in whatever way we acquire the two images of a scene. A system that can acquire two images of a scene can be realized, for instance in two shots using a digital camera and a filter, or in a single shot using a stereo camera, or a custom color filter array design. Simulation experiments using a stereo camera based system confirms the effectiveness of the proposed method. This could be useful in many imaging applications and computer vision.

© 2014 Optical Society of America

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2012 (1)

R. Shrestha, J. Y. Hardeberg, “Computational color constancy using chromagenic filters in color filter arrays,” in “Sensors, Cameras, and Systems for Industrial/Scientific Applications XIII,” Proc. SPIE 8298, 82980S (2012).
[CrossRef]

2011 (1)

R. Shrestha, A. Mansouri, J. Y. Hardeberg, “Multispectral imaging using a stereo camera: Concept, design and assessment,” EURASIP J. Adv. Sig. Pr. 2011(1), 57 (2011).
[CrossRef]

2010 (1)

F. Yasuma, T. Mitsunaga, D. Iso, S. Nayar, “Generalized assorted pixel camera: Postcapture control of resolution, dynamic range, and spectrum,” IEEE T. Image Process. 19(9), 2241–2253 (2010).
[CrossRef]

2008 (1)

C. Fredembach, G. D. Finlayson, “The bright-chromagenic algorithm for illuminant estimation,” J. Imaging Sci. Techn. 52(4), 0409061–04090811 (2008).
[CrossRef]

2007 (1)

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera,” Color Res. Appl. 32(5), 352–360 (2007).
[CrossRef]

2006 (3)

L. Miao, H. Qi, “The design and evaluation of a generic method for generating mosaicked multispectral filter arrays,” IEEE Trans. Image Process. 15(9), 2780–2791 (2006).
[CrossRef] [PubMed]

N. Tsumura, “Appearance reproduction and multispectral imaging,” Color Res. Appl. 31(4), 270–277 (2006).
[CrossRef]

S. D. Hordley, G. D. Finlayson, “Re-evaluation of color constancy algorithm performance,” J. Opt. Soc. Am. A 23(5), 1008–1020 (2006).
[CrossRef]

2005 (1)

D. R. Connah, J. Y. Hardeberg, “Spectral recovery using polynomial models,” in “Color Imaging X: Processing, Hardcopy, and Applications,” Proc. SPIE 5667, 65–75 (2005).
[CrossRef]

2002 (3)

K. Barnard, V. C. Cardei, B. Funt, “A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11(9), 972–984 (2002).
[CrossRef]

V. C. Cardei, B. Funt, K. Barnard, “Estimating the scene illumination chromaticity by using a neural network,” J. Opt. Soc. Am. A 19(12), 2374–2386 (2002).
[CrossRef]

J. Y. Hardeberg, F. Schmitt, H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41(10), 2532–2548 (2002).
[CrossRef]

2001 (1)

G. D. Finlayson, S. D. Hordley, P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. 23(11), 1209–1221 (2001).
[CrossRef]

1999 (1)

S. Tominaga, “Spectral imaging by a multichannel camera,” J. Electronic Imaging 8(4), 332–341 (1999).
[CrossRef]

1997 (1)

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

1990 (1)

D. A. Forsyth, “A novel algorithm for color constancy,” Int. J. Comput. Vision 5(1), 5–36 (1990).
[CrossRef]

1980 (1)

G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin I. 310(1), 1–26 (1980).
[CrossRef]

1977 (1)

E. H. Land, “The retinex theory of color vision,” Sci. Am. 237(6), 108–128 (1977).
[CrossRef] [PubMed]

Amano, K.

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera,” Color Res. Appl. 32(5), 352–360 (2007).
[CrossRef]

Barnard, K.

K. Barnard, V. C. Cardei, B. Funt, “A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11(9), 972–984 (2002).
[CrossRef]

V. C. Cardei, B. Funt, K. Barnard, “Estimating the scene illumination chromaticity by using a neural network,” J. Opt. Soc. Am. A 19(12), 2374–2386 (2002).
[CrossRef]

Blake, A.

P. V. Gehler, C. Rother, A. Blake, T. Minka, T. Sharp, “Bayesian color constancy revisited,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2008), 1–8.

Boust, C.

R. Shrestha, J. Hardeberg, C. Boust, “LED based multispectral film scanner for accurate color imaging,” in Proceedings of the 8th International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), 811–817.

Brettel, H.

J. Y. Hardeberg, F. Schmitt, H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41(10), 2532–2548 (2002).
[CrossRef]

Buchsbaum, G.

G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin I. 310(1), 1–26 (1980).
[CrossRef]

Cardei, V. C.

K. Barnard, V. C. Cardei, B. Funt, “A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11(9), 972–984 (2002).
[CrossRef]

V. C. Cardei, B. Funt, K. Barnard, “Estimating the scene illumination chromaticity by using a neural network,” J. Opt. Soc. Am. A 19(12), 2374–2386 (2002).
[CrossRef]

Connah, D. R.

D. R. Connah, J. Y. Hardeberg, “Spectral recovery using polynomial models,” in “Color Imaging X: Processing, Hardcopy, and Applications,” Proc. SPIE 5667, 65–75 (2005).
[CrossRef]

D. R. Connah, J. Y. Hardeberg, S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2004), 1497–1500.

Day, E. A.

F. H. Imai, L. A. Taplin, E. A. Day, “Comparative study of spectral reflectance estimation based on broadband imaging systems,” in Tech. rep., Center for Imaging Science, Munsell Color Science Laboratory, Rochester Institute of Technology, Rochester, New York, USA (2003).

Finlayson, G. D.

C. Fredembach, G. D. Finlayson, “The bright-chromagenic algorithm for illuminant estimation,” J. Imaging Sci. Techn. 52(4), 0409061–04090811 (2008).
[CrossRef]

S. D. Hordley, G. D. Finlayson, “Re-evaluation of color constancy algorithm performance,” J. Opt. Soc. Am. A 23(5), 1008–1020 (2006).
[CrossRef]

G. D. Finlayson, S. D. Hordley, P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. 23(11), 1209–1221 (2001).
[CrossRef]

G. D. Finlayson, S. D. Hordley, P. Morovic, “Chromagenic colour constancy,” in Proceedings of the 10th Congress of the International Colour Association (AIC, 2005), 8–13.

Forsyth, D. A.

D. A. Forsyth, “A novel algorithm for color constancy,” Int. J. Comput. Vision 5(1), 5–36 (1990).
[CrossRef]

Foster, D. H.

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera,” Color Res. Appl. 32(5), 352–360 (2007).
[CrossRef]

Fredembach, C.

C. Fredembach, G. D. Finlayson, “The bright-chromagenic algorithm for illuminant estimation,” J. Imaging Sci. Techn. 52(4), 0409061–04090811 (2008).
[CrossRef]

Funt, B.

V. C. Cardei, B. Funt, K. Barnard, “Estimating the scene illumination chromaticity by using a neural network,” J. Opt. Soc. Am. A 19(12), 2374–2386 (2002).
[CrossRef]

K. Barnard, V. C. Cardei, B. Funt, “A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data,” IEEE Trans. Image Process. 11(9), 972–984 (2002).
[CrossRef]

Gehler, P. V.

P. V. Gehler, C. Rother, A. Blake, T. Minka, T. Sharp, “Bayesian color constancy revisited,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2008), 1–8.

Gouton, P.

A. M. Mansouri, F. S. Marzani, P. Gouton, “Neural networks in two cascade algorithms for spectral reflectance reconstruction,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2005), 2053–2056.

Grossberg, M. D. D.

J. I. Park, M. H. Lee, M. D. D. Grossberg, S. K. Nayar, “Multispectral imaging using multiplexed illumination,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 2007), 1–8.

Hardeberg, J.

R. Shrestha, J. Hardeberg, C. Boust, “LED based multispectral film scanner for accurate color imaging,” in Proceedings of the 8th International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), 811–817.

R. Shrestha, J. Hardeberg, “CFA based simultaneous multispectral imaging and illuminant estimation,” in Proceedings of the 4th Computational Color Imaging Workshop, Vol. 7786 of LNCS (Springer, 2013), 158–170.
[CrossRef]

Hardeberg, J. Y.

R. Shrestha, J. Y. Hardeberg, “Computational color constancy using chromagenic filters in color filter arrays,” in “Sensors, Cameras, and Systems for Industrial/Scientific Applications XIII,” Proc. SPIE 8298, 82980S (2012).
[CrossRef]

R. Shrestha, A. Mansouri, J. Y. Hardeberg, “Multispectral imaging using a stereo camera: Concept, design and assessment,” EURASIP J. Adv. Sig. Pr. 2011(1), 57 (2011).
[CrossRef]

D. R. Connah, J. Y. Hardeberg, “Spectral recovery using polynomial models,” in “Color Imaging X: Processing, Hardcopy, and Applications,” Proc. SPIE 5667, 65–75 (2005).
[CrossRef]

J. Y. Hardeberg, F. Schmitt, H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41(10), 2532–2548 (2002).
[CrossRef]

R. Shrestha, J. Y. Hardeberg, “Multispectral imaging using LED illumination and an RGB camera,” in Proceedings of the 21st Color and Imaging Conference on Color Science and Engineering Systems, Technologies, and Applications (IS&T, 2013), 8–13.

D. R. Connah, J. Y. Hardeberg, S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2004), 1497–1500.

R. Shrestha, J. Y. Hardeberg, “Simultaneous multispectral imaging and illuminant estimation using a stereo camera,” in Proceedings of the 5th International Conference on Image and Signal Processing,Vol. 7340 of LNCS (Springer, 2012), 45–55.

R. Shrestha, J. Y. Hardeberg, “Computational color constancy using a stereo camera,” in Proceedings of the 6th European Conference on Colour in Graphics, Imaging, and Vision (IS&T, 2012), 69–74.

Hordley, S. D.

S. D. Hordley, G. D. Finlayson, “Re-evaluation of color constancy algorithm performance,” J. Opt. Soc. Am. A 23(5), 1008–1020 (2006).
[CrossRef]

G. D. Finlayson, S. D. Hordley, P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. 23(11), 1209–1221 (2001).
[CrossRef]

G. D. Finlayson, S. D. Hordley, P. Morovic, “Chromagenic colour constancy,” in Proceedings of the 10th Congress of the International Colour Association (AIC, 2005), 8–13.

Hubel, P. M.

G. D. Finlayson, S. D. Hordley, P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. 23(11), 1209–1221 (2001).
[CrossRef]

Imai, F. H.

F. H. Imai, L. A. Taplin, E. A. Day, “Comparative study of spectral reflectance estimation based on broadband imaging systems,” in Tech. rep., Center for Imaging Science, Munsell Color Science Laboratory, Rochester Institute of Technology, Rochester, New York, USA (2003).

Iso, D.

F. Yasuma, T. Mitsunaga, D. Iso, S. Nayar, “Generalized assorted pixel camera: Postcapture control of resolution, dynamic range, and spectrum,” IEEE T. Image Process. 19(9), 2241–2253 (2010).
[CrossRef]

Iwama, R.

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

Komiya, Y.

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

Land, E. H.

E. H. Land, “The retinex theory of color vision,” Sci. Am. 237(6), 108–128 (1977).
[CrossRef] [PubMed]

Lee, M. H.

J. I. Park, M. H. Lee, M. D. D. Grossberg, S. K. Nayar, “Multispectral imaging using multiplexed illumination,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 2007), 1–8.

Mansouri, A.

R. Shrestha, A. Mansouri, J. Y. Hardeberg, “Multispectral imaging using a stereo camera: Concept, design and assessment,” EURASIP J. Adv. Sig. Pr. 2011(1), 57 (2011).
[CrossRef]

Mansouri, A. M.

A. M. Mansouri, F. S. Marzani, P. Gouton, “Neural networks in two cascade algorithms for spectral reflectance reconstruction,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2005), 2053–2056.

Marzani, F. S.

A. M. Mansouri, F. S. Marzani, P. Gouton, “Neural networks in two cascade algorithms for spectral reflectance reconstruction,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2005), 2053–2056.

Miao, L.

L. Miao, H. Qi, “The design and evaluation of a generic method for generating mosaicked multispectral filter arrays,” IEEE Trans. Image Process. 15(9), 2780–2791 (2006).
[CrossRef] [PubMed]

Minka, T.

P. V. Gehler, C. Rother, A. Blake, T. Minka, T. Sharp, “Bayesian color constancy revisited,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2008), 1–8.

Mitsunaga, T.

F. Yasuma, T. Mitsunaga, D. Iso, S. Nayar, “Generalized assorted pixel camera: Postcapture control of resolution, dynamic range, and spectrum,” IEEE T. Image Process. 19(9), 2241–2253 (2010).
[CrossRef]

Morovic, P.

G. D. Finlayson, S. D. Hordley, P. Morovic, “Chromagenic colour constancy,” in Proceedings of the 10th Congress of the International Colour Association (AIC, 2005), 8–13.

Nascimento, S. M. C.

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera,” Color Res. Appl. 32(5), 352–360 (2007).
[CrossRef]

Nayar, S.

F. Yasuma, T. Mitsunaga, D. Iso, S. Nayar, “Generalized assorted pixel camera: Postcapture control of resolution, dynamic range, and spectrum,” IEEE T. Image Process. 19(9), 2241–2253 (2010).
[CrossRef]

Nayar, S. K.

J. I. Park, M. H. Lee, M. D. D. Grossberg, S. K. Nayar, “Multispectral imaging using multiplexed illumination,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 2007), 1–8.

Nieves, J. L.

E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano, D. H. Foster, “Recovering spectral data from natural scenes with an RGB digital camera,” Color Res. Appl. 32(5), 352–360 (2007).
[CrossRef]

Obi, T.

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

Ohya, Y.

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

Ohyama, N.

M. Yamaguchi, R. Iwama, Y. Ohya, T. Obi, N. Ohyama, Y. Komiya, T. Wada, “Natural color reproduction in the television system for telemedicime,” in “Medical Imaging: Image Display,” Proc. SPIE 3031, 482–489 (1997).
[CrossRef]

Park, J. I.

J. I. Park, M. H. Lee, M. D. D. Grossberg, S. K. Nayar, “Multispectral imaging using multiplexed illumination,” in Proceedings of IEEE Conference on Computer Vision (IEEE, 2007), 1–8.

Qi, H.

L. Miao, H. Qi, “The design and evaluation of a generic method for generating mosaicked multispectral filter arrays,” IEEE Trans. Image Process. 15(9), 2780–2791 (2006).
[CrossRef] [PubMed]

Rother, C.

P. V. Gehler, C. Rother, A. Blake, T. Minka, T. Sharp, “Bayesian color constancy revisited,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2008), 1–8.

Schmitt, F.

J. Y. Hardeberg, F. Schmitt, H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41(10), 2532–2548 (2002).
[CrossRef]

Sharp, T.

P. V. Gehler, C. Rother, A. Blake, T. Minka, T. Sharp, “Bayesian color constancy revisited,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2008), 1–8.

Shrestha, R.

R. Shrestha, J. Y. Hardeberg, “Computational color constancy using chromagenic filters in color filter arrays,” in “Sensors, Cameras, and Systems for Industrial/Scientific Applications XIII,” Proc. SPIE 8298, 82980S (2012).
[CrossRef]

R. Shrestha, A. Mansouri, J. Y. Hardeberg, “Multispectral imaging using a stereo camera: Concept, design and assessment,” EURASIP J. Adv. Sig. Pr. 2011(1), 57 (2011).
[CrossRef]

R. Shrestha, J. Hardeberg, “CFA based simultaneous multispectral imaging and illuminant estimation,” in Proceedings of the 4th Computational Color Imaging Workshop, Vol. 7786 of LNCS (Springer, 2013), 158–170.
[CrossRef]

R. Shrestha, J. Hardeberg, C. Boust, “LED based multispectral film scanner for accurate color imaging,” in Proceedings of the 8th International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), 811–817.

R. Shrestha, J. Y. Hardeberg, “Multispectral imaging using LED illumination and an RGB camera,” in Proceedings of the 21st Color and Imaging Conference on Color Science and Engineering Systems, Technologies, and Applications (IS&T, 2013), 8–13.

R. Shrestha, J. Y. Hardeberg, “Computational color constancy using a stereo camera,” in Proceedings of the 6th European Conference on Colour in Graphics, Imaging, and Vision (IS&T, 2012), 69–74.

R. Shrestha, J. Y. Hardeberg, “Simultaneous multispectral imaging and illuminant estimation using a stereo camera,” in Proceedings of the 5th International Conference on Image and Signal Processing,Vol. 7340 of LNCS (Springer, 2012), 45–55.

Taplin, L. A.

F. H. Imai, L. A. Taplin, E. A. Day, “Comparative study of spectral reflectance estimation based on broadband imaging systems,” in Tech. rep., Center for Imaging Science, Munsell Color Science Laboratory, Rochester Institute of Technology, Rochester, New York, USA (2003).

Tominaga, S.

S. Tominaga, “Spectral imaging by a multichannel camera,” J. Electronic Imaging 8(4), 332–341 (1999).
[CrossRef]

Tsumura, N.

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Figures (7)

Fig. 1
Fig. 1

Framework for the spectrogenic imaging system.

Fig. 2
Fig. 2

Spectral transmittance of the Omega XF1078 filter.

Fig. 3
Fig. 3

Spectral sensitivities of the individual cameras, and the 6-channel multispectral system.

Fig. 4
Fig. 4

RGB images rendered using four publicly available hyperspectral images from the Joensuu Spectral Image Database [30] (URL: http://www.uef.fi/fi/spectral/spectral-image-database), University of Eastern Finland.

Fig. 5
Fig. 5

The RGB images captured under the four test illuminants (Odd column: measured, Even column: estimated). In most of the cases, the images rendered under the estimated illuminants are very close to the ground truth.

Fig. 6
Fig. 6

Reflectance spectra at five different pixels in the four test images, acquired under illuminant A. The pixel locations [row column], are shown above the plots.

Fig. 7
Fig. 7

Reflectance spectra at the same five pixels (as in Fig. 6) in the four test images, acquired under illuminant D65. The pixel locations [row column], are shown above the plots.

Tables (1)

Tables Icon

Table 1 Evaluation metric values for each of the test illuminant

Equations (9)

Equations on this page are rendered with MathJax. Learn more.

C N = S T L R + n N
and C F = S T F L R + n F ,
C F M I E C N ,
M I E = C F C N + ,
M I E = C p , F C p , N + .
est = argmin i ( e i ) , i = 1 , , m ,
e i = M I E , i C p , N C p , F .
R est = M S E C p ,
M S E = R train C p , train + ,

Metrics