Abstract

Colorimetric evaluation of an image acquisition device is important for evaluating and optimizing a set of sensors. We have already proposed a colorimetric evaluation model [J. Imaging Sci. Technol. 49, 588–593 (2005)JIMTE61062-3701] based on the Wiener estimation. The mean square errors (MSE) between the estimated and the actual fundamental vectors by the Wiener filter and the proposed colorimetric quality (Qc) agree quite well with the proposed model and we have shown that the estimation of the system noise variance of the image acquisition system is essential for the evaluation model. In this paper, it is confirmed that the proposed model can be applied to two different reflectance recovery models, and these models provide us an easy method for estimating the proposed colorimetric quality (Qc). The influence of the system noise originates from the sampling intervals of the spectral characteristics of the sensors, the illuminations and the reflectance and the quantization error on the evaluation model are studied and it is confirmed from the experimental results that the proposed model holds even in a noisy condition.

© 2009 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. Y. Miyake and Y. Yokoyama, “Obtaining and reproduction of accurate color images based on human perception,” Proc. SPIE 3300, 190-197 (1998).
    [CrossRef]
  2. H. Haneishi, T. Hasegawa, N. A. Hosoi, Y. Yokoyama, N. Tsumura, and Y. Miyake, “System design for accurately estimating the spectral reflectance of art paintings,” Appl. Opt. 39, 6621-6632 (2000).
    [CrossRef]
  3. Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.
  4. K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
    [CrossRef]
  5. A. A. Afifi and S. P. Azen, Statistical Analysis: A Computer Oriented Approach (Academic Press, 1972), Chap. 3.
  6. H. L. Shen and J. H. Xin, “Spectral characterization of a color scanner based on optimized adaptive estimation,” J. Opt. Soc. Am. A 23, 1566-1569 (2006).
    [CrossRef]
  7. D. Connah, J. Y. Hardeberg, and S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in ICIP '04, 2004 International Conference on Image Processing (IEEE, 2004), pp. 1497-1500.
    [CrossRef]
  8. Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36
  9. D. Connah and J. Y. Hardeberg, “Spectral recovery using polynomial models,” Proc. SPIE 5667, 65-75 (2005).
    [CrossRef]
  10. M. A. López-Álvarez, J. Hernández-Andrés, J. Romero, F. J. Olmo, A. Cazorla, and L. Alados-Arboledas, “Using a trichromatic CCD camera for spectral skylight estimation,” Appl. Opt. 47, H31-H38 (2008).
    [CrossRef] [PubMed]
  11. F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in Proceeding of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42-49.
  12. M. A. López-Álvarez, J. Hernández-Andrés, Eva. M. Valero, and J. Romero, “Selecting algorithms, sensors and liner bases for optimum spectral recovery of skylight,” J. Opt. Soc. Am. A 24, 942-956 (2007).
    [CrossRef]
  13. V. Cheung, S. Westland, C. Li, J. Hardeberg, and D. Connah, “Characterization of trichromatic color cameras by using a new multispectral imaging technique,” J. Opt. Soc. Am. A 22, 1231-1240 (2005).
    [CrossRef]
  14. M. Shi and G. Healey, “Using reflectance models for color scanner calibration,” J. Opt. Soc. Am. A 19, 645-656(2002).
    [CrossRef]
  15. J. Cohen, “Dependency of spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369-370(1964).
  16. L. T. Maloney, “Evaluation of linear models of surface spectral reflectance with small numbers of parameters,” J. Opt. Soc. Am. A 3, 1673-1683 (1986).
    [CrossRef] [PubMed]
  17. J. P. S. Parkkinen, J. Hallikainen, and T. Jaaskelainen, “Characteristic spectra of Munsell colors,” J. Opt. Soc. Am. A 6, 318-322 (1989).
    [CrossRef]
  18. R. Piché, “Nonnegative color spectrum analysis filters from principal component analysis characteristic spectra,” J. Opt. Soc. Am. A 19, 1946-1950 (2002).
    [CrossRef]
  19. M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.
  20. P. S. Hung, “Colorimetric calibration for scanners and media,” Proc. SPIE 1448, 164-174 (1991).
    [CrossRef]
  21. H. R. Kang, “Colorimetric scanner calibration,” J. Imaging Sci. Technol. 36, 162-170 (1992).
  22. H. E. J. Neugebauer “Quality factor for filters whose spectral transmittances are different from color mixture curves, and its application to color photography,” J. Opt. Soc. Am. 46, 821-824 (1956).
    [CrossRef]
  23. P. L. Vora and H. J. Trussell, “Measure of goodness of a set of color-scanning filters,” J. Opt. Soc. Am. A 10, 1499-1508(1993).
    [CrossRef]
  24. G. Sharma and H. J. Trussell, “Figure of merit for color scanners,” IEEE Trans. Image Process. 6, 990-1001 (1997).
    [CrossRef]
  25. N. Shimano, “Suppression of noise effect in color corrections by spectral sensitivities of image sensors,” Opt. Rev. 9, 81-88(2002).
    [CrossRef]
  26. N. Shimano, “Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise,” Opt. Eng. 45, 013201 (2006).
    [CrossRef]
  27. G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
    [CrossRef]
  28. N. Shimano, “Application of a colorimetric evaluation model to multispectral color image acquisition systems,” J. Imaging Sci. Technol. 49, 588-593 (2005).
  29. N. Shimano, “Evaluation of a multispectral image acquisition system aimed at reconstruction of spectral reflectances,” Opt. Eng. 44, 107005 (2005).
    [CrossRef]
  30. J. B. Cohen, “Color and color mixture: scalar and vector fundamentals,” Color Res. Appl. 13, 5-39 (1988).
    [CrossRef]
  31. W. A. Shapiro, “Generalization of tristimulus coordinates,” J. Opt. Soc. Am. 56, 795-801 (1966).
    [CrossRef]
  32. A. Rosenfeld and A. C. Kak, Digital Picture Processing, 2nd ed. (Academic Press, 1982).
  33. N. Shimano, “Recovery of spectral reflectances of objects being imaged without prior knowledge,” IEEE Trans. Image Process. 15, 1848-1856 (2006).
    [CrossRef]
  34. M. Hironaga and N. Shimano, “Evaluating the quality of an image acquisition device aimed at the reconstruction of spectral reflectances using recovery models,” J. Imaging Sci. Technol. 52, 030503 (2008).
    [CrossRef]
  35. G. H. Golub and C. F. V. Loan, Matrix Computations, 3rd ed. (Johns Hopkins University, 1996), p. 55.
  36. M. A. López-Álvarez, J. Hernández-Andrés, and J. Romero, “Developing an optimum computer-designed multispectral system comprising a monochrome CCD camera and a liquid-crystal tunable filter,” Appl. Opt. 47, 4381-4390 (2008).
    [CrossRef] [PubMed]

2008 (3)

2007 (1)

2006 (3)

H. L. Shen and J. H. Xin, “Spectral characterization of a color scanner based on optimized adaptive estimation,” J. Opt. Soc. Am. A 23, 1566-1569 (2006).
[CrossRef]

N. Shimano, “Recovery of spectral reflectances of objects being imaged without prior knowledge,” IEEE Trans. Image Process. 15, 1848-1856 (2006).
[CrossRef]

N. Shimano, “Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise,” Opt. Eng. 45, 013201 (2006).
[CrossRef]

2005 (4)

N. Shimano, “Application of a colorimetric evaluation model to multispectral color image acquisition systems,” J. Imaging Sci. Technol. 49, 588-593 (2005).

N. Shimano, “Evaluation of a multispectral image acquisition system aimed at reconstruction of spectral reflectances,” Opt. Eng. 44, 107005 (2005).
[CrossRef]

D. Connah and J. Y. Hardeberg, “Spectral recovery using polynomial models,” Proc. SPIE 5667, 65-75 (2005).
[CrossRef]

V. Cheung, S. Westland, C. Li, J. Hardeberg, and D. Connah, “Characterization of trichromatic color cameras by using a new multispectral imaging technique,” J. Opt. Soc. Am. A 22, 1231-1240 (2005).
[CrossRef]

2002 (4)

M. Shi and G. Healey, “Using reflectance models for color scanner calibration,” J. Opt. Soc. Am. A 19, 645-656(2002).
[CrossRef]

R. Piché, “Nonnegative color spectrum analysis filters from principal component analysis characteristic spectra,” J. Opt. Soc. Am. A 19, 1946-1950 (2002).
[CrossRef]

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

N. Shimano, “Suppression of noise effect in color corrections by spectral sensitivities of image sensors,” Opt. Rev. 9, 81-88(2002).
[CrossRef]

2000 (1)

1998 (2)

Y. Miyake and Y. Yokoyama, “Obtaining and reproduction of accurate color images based on human perception,” Proc. SPIE 3300, 190-197 (1998).
[CrossRef]

G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
[CrossRef]

1997 (1)

G. Sharma and H. J. Trussell, “Figure of merit for color scanners,” IEEE Trans. Image Process. 6, 990-1001 (1997).
[CrossRef]

1993 (1)

1992 (1)

H. R. Kang, “Colorimetric scanner calibration,” J. Imaging Sci. Technol. 36, 162-170 (1992).

1991 (1)

P. S. Hung, “Colorimetric calibration for scanners and media,” Proc. SPIE 1448, 164-174 (1991).
[CrossRef]

1989 (1)

1988 (1)

J. B. Cohen, “Color and color mixture: scalar and vector fundamentals,” Color Res. Appl. 13, 5-39 (1988).
[CrossRef]

1986 (1)

1966 (1)

1964 (1)

J. Cohen, “Dependency of spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369-370(1964).

1956 (1)

Afifi, A. A.

A. A. Afifi and S. P. Azen, Statistical Analysis: A Computer Oriented Approach (Academic Press, 1972), Chap. 3.

Alados-Arboledas, L.

Azen, S. P.

A. A. Afifi and S. P. Azen, Statistical Analysis: A Computer Oriented Approach (Academic Press, 1972), Chap. 3.

Berns, R. S.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in Proceeding of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42-49.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36

Cazorla, A.

Cheung, V.

Cohen, J.

J. Cohen, “Dependency of spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369-370(1964).

Cohen, J. B.

J. B. Cohen, “Color and color mixture: scalar and vector fundamentals,” Color Res. Appl. 13, 5-39 (1988).
[CrossRef]

Connah, D.

V. Cheung, S. Westland, C. Li, J. Hardeberg, and D. Connah, “Characterization of trichromatic color cameras by using a new multispectral imaging technique,” J. Opt. Soc. Am. A 22, 1231-1240 (2005).
[CrossRef]

D. Connah and J. Y. Hardeberg, “Spectral recovery using polynomial models,” Proc. SPIE 5667, 65-75 (2005).
[CrossRef]

D. Connah, J. Y. Hardeberg, and S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in ICIP '04, 2004 International Conference on Image Processing (IEEE, 2004), pp. 1497-1500.
[CrossRef]

Cupitt, J.

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

Golub, G. H.

G. H. Golub and C. F. V. Loan, Matrix Computations, 3rd ed. (Johns Hopkins University, 1996), p. 55.

Hallikainen, J.

Haneishi, H.

Hardeberg, J.

Hardeberg, J. Y.

D. Connah and J. Y. Hardeberg, “Spectral recovery using polynomial models,” Proc. SPIE 5667, 65-75 (2005).
[CrossRef]

D. Connah, J. Y. Hardeberg, and S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in ICIP '04, 2004 International Conference on Image Processing (IEEE, 2004), pp. 1497-1500.
[CrossRef]

Hasegawa, T.

Healey, G.

Hernández-Andrés, J.

Hironaga, M.

M. Hironaga and N. Shimano, “Evaluating the quality of an image acquisition device aimed at the reconstruction of spectral reflectances using recovery models,” J. Imaging Sci. Technol. 52, 030503 (2008).
[CrossRef]

Hosoi, N. A.

Hung, P. S.

P. S. Hung, “Colorimetric calibration for scanners and media,” Proc. SPIE 1448, 164-174 (1991).
[CrossRef]

Imai, F. H.

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in Proceeding of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42-49.

Jaaskelainen, T.

Kak, A. C.

A. Rosenfeld and A. C. Kak, Digital Picture Processing, 2nd ed. (Academic Press, 1982).

Kang, H. R.

H. R. Kang, “Colorimetric scanner calibration,” J. Imaging Sci. Technol. 36, 162-170 (1992).

Li, C.

Loan, C. F. V.

G. H. Golub and C. F. V. Loan, Matrix Computations, 3rd ed. (Johns Hopkins University, 1996), p. 55.

López-Álvarez, M. A.

Mahy, M.

M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.

Maloney, L. T.

Martinez, K.

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

Miyake, Y.

Neugebauer, H. E. J.

Nezamabadi, M.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.

Olmo, F. J.

Oosterlinck, A.

M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.

Parkkinen, J. P. S.

Piché, R.

Pillay, R.

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

Romero, J.

Rosenfeld, A.

A. Rosenfeld and A. C. Kak, Digital Picture Processing, 2nd ed. (Academic Press, 1982).

Saunders, D.

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

Shapiro, W. A.

Sharma, G.

G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
[CrossRef]

G. Sharma and H. J. Trussell, “Figure of merit for color scanners,” IEEE Trans. Image Process. 6, 990-1001 (1997).
[CrossRef]

Shen, H. L.

Shi, M.

Shimano, N.

M. Hironaga and N. Shimano, “Evaluating the quality of an image acquisition device aimed at the reconstruction of spectral reflectances using recovery models,” J. Imaging Sci. Technol. 52, 030503 (2008).
[CrossRef]

N. Shimano, “Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise,” Opt. Eng. 45, 013201 (2006).
[CrossRef]

N. Shimano, “Recovery of spectral reflectances of objects being imaged without prior knowledge,” IEEE Trans. Image Process. 15, 1848-1856 (2006).
[CrossRef]

N. Shimano, “Evaluation of a multispectral image acquisition system aimed at reconstruction of spectral reflectances,” Opt. Eng. 44, 107005 (2005).
[CrossRef]

N. Shimano, “Application of a colorimetric evaluation model to multispectral color image acquisition systems,” J. Imaging Sci. Technol. 49, 588-593 (2005).

N. Shimano, “Suppression of noise effect in color corrections by spectral sensitivities of image sensors,” Opt. Rev. 9, 81-88(2002).
[CrossRef]

Taplin, L. A.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.

Trussell, H. J.

G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
[CrossRef]

G. Sharma and H. J. Trussell, “Figure of merit for color scanners,” IEEE Trans. Image Process. 6, 990-1001 (1997).
[CrossRef]

P. L. Vora and H. J. Trussell, “Measure of goodness of a set of color-scanning filters,” J. Opt. Soc. Am. A 10, 1499-1508(1993).
[CrossRef]

Tsumura, N.

Valero, Eva. M.

Van Eycken, L.

M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.

Vora, P. L.

Vrhel, M. J.

G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
[CrossRef]

Wambacq, P.

M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.

Westland, S.

V. Cheung, S. Westland, C. Li, J. Hardeberg, and D. Connah, “Characterization of trichromatic color cameras by using a new multispectral imaging technique,” J. Opt. Soc. Am. A 22, 1231-1240 (2005).
[CrossRef]

D. Connah, J. Y. Hardeberg, and S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in ICIP '04, 2004 International Conference on Image Processing (IEEE, 2004), pp. 1497-1500.
[CrossRef]

Xin, J. H.

Yokoyama, Y.

Zhao, Y.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36

Appl. Opt. (3)

Color Res. Appl. (1)

J. B. Cohen, “Color and color mixture: scalar and vector fundamentals,” Color Res. Appl. 13, 5-39 (1988).
[CrossRef]

IEEE Trans. Image Process. (3)

G. Sharma and H. J. Trussell, “Figure of merit for color scanners,” IEEE Trans. Image Process. 6, 990-1001 (1997).
[CrossRef]

G. Sharma, H. J. Trussell, and M. J. Vrhel, “Optimal nonnegative color scanning filters,” IEEE Trans. Image Process. 7, 129-133 (1998).
[CrossRef]

N. Shimano, “Recovery of spectral reflectances of objects being imaged without prior knowledge,” IEEE Trans. Image Process. 15, 1848-1856 (2006).
[CrossRef]

J. Imaging Sci. Technol. (3)

M. Hironaga and N. Shimano, “Evaluating the quality of an image acquisition device aimed at the reconstruction of spectral reflectances using recovery models,” J. Imaging Sci. Technol. 52, 030503 (2008).
[CrossRef]

H. R. Kang, “Colorimetric scanner calibration,” J. Imaging Sci. Technol. 36, 162-170 (1992).

N. Shimano, “Application of a colorimetric evaluation model to multispectral color image acquisition systems,” J. Imaging Sci. Technol. 49, 588-593 (2005).

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (8)

Opt. Eng. (2)

N. Shimano, “Evaluation of a multispectral image acquisition system aimed at reconstruction of spectral reflectances,” Opt. Eng. 44, 107005 (2005).
[CrossRef]

N. Shimano, “Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise,” Opt. Eng. 45, 013201 (2006).
[CrossRef]

Opt. Rev. (1)

N. Shimano, “Suppression of noise effect in color corrections by spectral sensitivities of image sensors,” Opt. Rev. 9, 81-88(2002).
[CrossRef]

Proc. IEEE (1)

K. Martinez, J. Cupitt, D. Saunders, and R. Pillay, “Ten years of art imaging research,” Proc. IEEE 90, 28-41 (2002).
[CrossRef]

Proc. SPIE (3)

D. Connah and J. Y. Hardeberg, “Spectral recovery using polynomial models,” Proc. SPIE 5667, 65-75 (2005).
[CrossRef]

Y. Miyake and Y. Yokoyama, “Obtaining and reproduction of accurate color images based on human perception,” Proc. SPIE 3300, 190-197 (1998).
[CrossRef]

P. S. Hung, “Colorimetric calibration for scanners and media,” Proc. SPIE 1448, 164-174 (1991).
[CrossRef]

Psychon. Sci. (1)

J. Cohen, “Dependency of spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369-370(1964).

Other (8)

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Using the Matrix R Method for spectral image archives,” AIC Colour 05: 10th Congress of the International Colour Association, J. L. Nieves and J. Hernández-Andrés, eds. (AIC, 2005), pp. 469-472.

F. H. Imai and R. S. Berns, “Spectral estimation using trichromatic digital cameras,” in Proceeding of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives (Society of Multispectral Imaging of Japan, 1999), pp. 42-49.

A. A. Afifi and S. P. Azen, Statistical Analysis: A Computer Oriented Approach (Academic Press, 1972), Chap. 3.

D. Connah, J. Y. Hardeberg, and S. Westland, “Comparison of linear spectral reconstruction methods for multispectral imaging,” in ICIP '04, 2004 International Conference on Image Processing (IEEE, 2004), pp. 1497-1500.
[CrossRef]

Y. Zhao, L. A. Taplin, M. Nezamabadi, and R. S. Berns, “Methods of spectral reflectance reconstruction for a Sinarback 54 digital camera,” Munsell Color Science Laboratory, Tech. Rep. (December, 2004), pp. 1-36

M. Mahy, P. Wambacq, L. Van Eycken, and A. Oosterlinck, “Optimal filters for the reconstruction and discrimination of reflectance curves,” in Second Color Imaging Conference: Color Science, Systems, and Applications (The Society for Imaging Science and Technology, 1994), pp. 140-143.

A. Rosenfeld and A. C. Kak, Digital Picture Processing, 2nd ed. (Academic Press, 1982).

G. H. Golub and C. F. V. Loan, Matrix Computations, 3rd ed. (Johns Hopkins University, 1996), p. 55.

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (8)

Fig. 1
Fig. 1

Spectral sensitivities of the sensors of the camera sampled at 1 nm .

Fig. 2
Fig. 2

Spectral power distribution of the illumination sampled at 1 nm .

Fig. 3
Fig. 3

MSEs of the recovered fundamental vectors by the Wiener, Regression, and Imai–Berns models for the Gretag Macbeth Color Checker (CC) and the Kodak Q60R1 (KK) are plotted as a function of Q c ( σ 2 ) .

Fig. 4
Fig. 4

MSEs of the recovered fundamental vectors by the Wiener, Regression, and Imai–Berns models for the GretagMacbeth ColorChecker (CC) are plotted as a function of Q c ( σ 2 ) with (a)  8   bit image and 10 nm sampling intervals, (b)  8   bit image and 20 nm sampling intervals, (c)  6   bit image and 10 nm sampling intervals, and (d)  6   bit image and 20 nm sampling intervals.

Fig. 5
Fig. 5

MSEs of the recovered fundamental vectors by the Wiener, Regression, and Imai–Berns models for the Gretag Macbeth Color Checker (CC) are plotted as a function of Q c ( 0 ) with 6   bit image and 10 nm sampling intervals [ MSE ( 0 ) s are plotted for the Wiener model].

Fig. 6
Fig. 6

MSEs of the recovered fundamental vectors by the Wiener, Regression, and Imai–Berns models for the GretagMacbeth ColorChecker (CC) and the theoretical MSE estimated with E max ( 1 Q c ( σ 2 ) ) with 10 nm sampling intervals are plotted as a function of the sampling bits.

Fig. 7
Fig. 7

10 nm NIF for three sensor sets are plotted as a function of the sampling bits.

Fig. 8
Fig. 8

Noise variance and the square of singular values for the sensor set “1234” and “247” with 8 and 6   bit images and 10 nm sampling intervals.

Equations (14)

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

p = S L o r + e ,
MSE = E { P v r P v r ^ 2 } ,
W 0 = R s s S L T ( S L R S S S L T + σ e 2 I ) 1 ,
MSE ( σ 2 ) = i = 1 α a i v 2 i = 1 α P CV a i v 2 + i = 1 α j = 1 β σ 2 κ j v 2 + σ 2 ( b j v T a i v ) 2 ,
MSE free = Σ i = 1 α a i v 2 Σ i = 1 α P CV a i v 2 ,
NIF = Σ i = 1 α Σ j = 1 β σ 2 κ j v 2 + σ 2 ( b j v T a i v ) 2 .
Q c ( σ 2 ) = Σ i = 1 α P CV a i v 2 Σ i = 1 α Σ j = 1 β σ 2 κ j v 2 + σ 2 ( b j v a i v ) 2 Σ i = 1 α a i v 2 .
MSE ( σ 2 ) = E max ( 1 Q c ( σ 2 ) ) ,
MSE ( 0 ) = Σ i = 1 α a i v 2 Σ i = 1 α P CV a i v 2 + Σ i = 1 α Σ j = 1 β σ 2 κ j v 2 ( b j v a i v ) 2 ,
σ ^ 2 MSE ( 0 ) MSE free Σ i = 1 α Σ j = 1 β ( b j v T a i v ) κ j v 2 .
W = F P + ,
B = Σ P + .
Q c ( 0 ) = Σ i = 1 α P CV a i v 2 Σ i = 1 α a i v 2 .
MSE ( σ 2 ) = MSE free + NIF ,

Metrics