Abstract

In multispectral imaging, the color accuracy of spectral reflectance estimation degrades significantly if the medium of test samples is different from that of calibration samples. This occurs mainly for two reasons, i.e., the different characteristics of spectral reflectances and the different measurement principles between an imaging system and a spectrophotometer. In this paper, this problem is referred to as cross-media instrument metamerism. We propose to correct it by using calibration samples from a standard color chart and a limited number of tuning samples with a target medium as a priori knowledge. The reflectance transform is computed by using both calibration and tuning samples, and the metamerism transform is calculated by modeling the correlation of camera responses between neighboring imaging channels. Experimental results show that the proposed method produces satisfactory spectral and colorimetric accuracy in reflectance estimation. The method could be deployed in practical applications when the available samples of certain media are inadequate for accurate reflectance estimation in a multispectral imaging system.

© 2011 Optical Society of America

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References

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  1. J. Hardeberg, “Acquisition and reproduction of color images: colorimetric and multispectral approaches,” Ph.D. dissertation (Ecole Nationale Superieure des Telecommunications, 1999).
  2. N. Shimano, “Recovery of spectral reflectances of objects being imaged without prior knowledge,” IEEE Trans. Image Process. 15, 1848–1856 (2006).
    [CrossRef] [PubMed]
  3. N. Shimano and M. Hironaga, “Recovery of spectral reflectances of imaged objects by the use of features of spectral reflectances,” J. Opt. Soc. Am. A 27, 251–258 (2010).
    [CrossRef]
  4. P. Urban, M. R. Rosen, and R. S. Berns, “Spectral image reconstruction using an edge preserving spatio-spectral wiener estimation,” J. Opt. Soc. Am. A 26, 1865–1875 (2009).
    [CrossRef]
  5. H. L. Shen, J. H. Xin, and S. J. Shao, “Improving reflectance reconstruction for multispectal imaging by combining different techniques,” Opt. Express 15, 5531–5536 (2007).
    [CrossRef] [PubMed]
  6. X-Rite Inc., http://www.xrite.com/.
  7. G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
    [CrossRef]
  8. H. L. Shen and J. H. Xin, “Colorimetric and spectral characterization of a color scanner using local statistics,” J. Imaging Sci. Technol. 48, 342–346 (2004).
  9. Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
    [CrossRef]
  10. Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
    [CrossRef]
  11. F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).
  12. W. K. Pratt, Digital Image Processing4th ed. (Wiley, 2007).
    [CrossRef]
  13. M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
    [CrossRef]

2010 (1)

2009 (1)

2007 (1)

2006 (1)

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

2004 (2)

H. L. Shen and J. H. Xin, “Colorimetric and spectral characterization of a color scanner using local statistics,” J. Imaging Sci. Technol. 48, 342–346 (2004).

Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
[CrossRef]

2001 (3)

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[CrossRef]

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
[CrossRef]

Berns, R. S.

Chung, Y. S.

Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
[CrossRef]

Cui, G.

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[CrossRef]

Ginsberg, I. W.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

Hardeberg, J.

J. Hardeberg, “Acquisition and reproduction of color images: colorimetric and multispectral approaches,” Ph.D. dissertation (Ecole Nationale Superieure des Telecommunications, 1999).

Hironaga, M.

Hong, G.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
[CrossRef]

Hsia, J. J.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

Komiya, Y.

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Limperis, T.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

Luo, M. R.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
[CrossRef]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[CrossRef]

Murakami, Y.

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Nicodemus, F. E.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

Obi, T.

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Ohyama, N.

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Pratt, W. K.

W. K. Pratt, Digital Image Processing4th ed. (Wiley, 2007).
[CrossRef]

Rhodes, P. A.

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
[CrossRef]

Richmond, J. C.

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

Rigg, B.

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[CrossRef]

Rosen, M. R.

Shao, S. J.

Shen, H. L.

H. L. Shen, J. H. Xin, and S. J. Shao, “Improving reflectance reconstruction for multispectal imaging by combining different techniques,” Opt. Express 15, 5531–5536 (2007).
[CrossRef] [PubMed]

H. L. Shen and J. H. Xin, “Colorimetric and spectral characterization of a color scanner using local statistics,” J. Imaging Sci. Technol. 48, 342–346 (2004).

Shimano, N.

N. Shimano and M. Hironaga, “Recovery of spectral reflectances of imaged objects by the use of features of spectral reflectances,” J. Opt. Soc. Am. A 27, 251–258 (2010).
[CrossRef]

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

Sin, K. M.

Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
[CrossRef]

Urban, P.

Xin, J. H.

H. L. Shen, J. H. Xin, and S. J. Shao, “Improving reflectance reconstruction for multispectal imaging by combining different techniques,” Opt. Express 15, 5531–5536 (2007).
[CrossRef] [PubMed]

Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
[CrossRef]

H. L. Shen and J. H. Xin, “Colorimetric and spectral characterization of a color scanner using local statistics,” J. Imaging Sci. Technol. 48, 342–346 (2004).

Yamaguchi, M.

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Color Res. Appl. (2)

G. Hong, M. R. Luo, and P. A. Rhodes, “A study of digital camera colorimetric characterization based on polynomial modeling,” Color Res. Appl. 26, 76–84 (2001).
[CrossRef]

M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Color Res. Appl. 26, 340–350 (2001).
[CrossRef]

Color Technol. (1)

Y. S. Chung, J. H. Xin, and K. M. Sin, “Improvement of inter-instrumental agreement for reflectance spectrophotometers,” Color Technol. 120, 284–292 (2004).
[CrossRef]

IEEE Trans. Image Process. (1)

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

J. Imaging Sci. Technol. (1)

H. L. Shen and J. H. Xin, “Colorimetric and spectral characterization of a color scanner using local statistics,” J. Imaging Sci. Technol. 48, 342–346 (2004).

J. Opt. Soc. Am. A (2)

Opt. Commun. (1)

Y. Murakami, T. Obi, M. Yamaguchi, N. Ohyama, and Y. Komiya, “Spectral reflectance estimation from multi-band image using color chart,” Opt. Commun. 188, 47–54 (2001).
[CrossRef]

Opt. Express (1)

Other (4)

J. Hardeberg, “Acquisition and reproduction of color images: colorimetric and multispectral approaches,” Ph.D. dissertation (Ecole Nationale Superieure des Telecommunications, 1999).

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometric considerations and nomenclature for reflectance,” Monograph 160 (National Institute of Standards and Technology, 1997).

W. K. Pratt, Digital Image Processing4th ed. (Wiley, 2007).
[CrossRef]

X-Rite Inc., http://www.xrite.com/.

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Figures (5)

Fig. 1
Fig. 1

Two samples with different media but identical reflectances produce different camera responses. (a) Spectral reflectance. (b) Multichannel camera responses.

Fig. 2
Fig. 2

Flowchart of the proposed instrument metamerism correction method.

Fig. 3
Fig. 3

CIE a * b * distributions of the (a) calibration samples, (b) tuning sample pool, and (c) test samples.

Fig. 4
Fig. 4

Distributions of spectral rms error with respect to the number of tuning samples L T . (a) 9-channel system. (b) 16-channel system.

Fig. 5
Fig. 5

Estimated reflectances of a Pantone test sample by different methods on the 16-channel system.

Tables (3)

Tables Icon

Table 1 Algorithm 1. Instrument Metamerism Correction

Tables Icon

Table 1 Specification of the Calibration, Tuning, and Test Samples Used in the Experiment

Tables Icon

Table 2 Spectral and Colorimetric Errors of the Proposed Method, Compared with Baseline Methods

Equations (21)

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

s ( λ ) = a 1 r ( λ 1 ) + a 2 r ( λ ) + a 3 r ( λ + 1 ) + a 4 ,
u k = λ m k ( λ ) r ( λ ) d λ + b k ,
u = Mr + b ,
r = W u ˜ ,
u ˜ = ( u 1 ) .
R = ( r 1 , r 2 , , r L A ) ,
U ˜ = ( u ˜ 1 , u ˜ 2 , , u ˜ L A ) .
R = W U ˜ ,
W = R U ˜ + ,
W = ( W s , w ) .
S = ( s 1 , s 2 , , s L T ) ,
V ˜ = ( v ˜ 1 , v ˜ 2 , , v ˜ L T ) ,
S = WD V ˜ ,
D = ( d 11 d 12 0 0 0 0 0 0 d ¯ 1 d 21 d 22 d 23 0 0 0 0 0 d ¯ 2 0 d 32 d 33 d 34 0 0 0 0 d ¯ 3 0 0 0 0 0 0 d K , K 1 d K , K d ¯ K 0 0 0 0 0 0 0 0 1 ) .
D = ( D s d 0 T 1 ) ,
( D s , d ) V ˜ = W s + ( S w 1 T ) ,
( R , η S ) = W ( U ˜ , η D V ˜ ) ,
η = ( L A L T ) 1 / 2 .
W = ( R , η S ) ( U ˜ , η D V ˜ ) + .
s ^ = WD v ˜ .
rms = ( ( s s ^ ) T ( s s ^ ) N ) 1 / 2 .

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