Abstract

Color enhancement of multispectral images is useful to visualize the image’s spectral features. Previously, a color enhancement method, which enhances the feature of a specified spectral band without changing the average color distribution, was proposed. However, sometimes the enhanced features are indiscernible or invisible, especially when the enhanced spectrum lies outside the visible range. In this paper, we extended the conventional method for more effective visualization of the spectral features both in visible range and non-visible range. In the proposed method, the user specifies both the spectral band for extracting the spectral feature and the color for visualization respectively, so that the spectral feature is enhanced with arbitrary color. The proposed color enhancement method was applied to different types of multispectral images where its effectiveness to visualize spectral features was verified.

© 2011 OSA

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  1. Z. Lee, K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch, “Hyperspectral remote sensing for shallow waters. I. A semianalytical model,” Appl. Opt. 37, 6329–6338 (1998).
    [CrossRef]
  2. J. A. Gualtieri and R. F. Cromp, “Support vector machines for hyperspectral remote sensing classification,” Proc. SPIE 3584, 221–232 (1999).
    [CrossRef]
  3. B.-C. Gao, M. J. Montes, Z. Ahmad, and C. O. Davis, “Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space,” Appl. Opt. 39, 887–896 (2000).
    [CrossRef]
  4. M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
    [CrossRef]
  5. J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Opt. Eng. 41, 2532–2548 (2002).
    [CrossRef]
  6. A. R. Gillespie, A. B. Kahle, and R. E. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches,” Remote Sens. Environ. 20, 209–235 (1986).
    [CrossRef]
  7. J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
    [CrossRef] [PubMed]
  8. M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
    [CrossRef]
  9. M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.
  10. 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]
  11. P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
    [CrossRef]
  12. N. Kosaka, K. Uto, and Y. Kosugi, “ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land,” IEEE Trans. Geosci. Remote Sens. 2, 220–224 (2005).
    [CrossRef]
  13. D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
    [CrossRef]
  14. D. Scribner, P. Warren, and J. Schuler, “Extending color vision methods to bands beyond the visible,” Machine Vision Appl. 11, 306–312 (2000).
    [CrossRef]
  15. M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).
  16. N. P. Jacobson and M. R. Gupta, “Design goals and solutions for display of hyperspectral images,” IEEE Trans. Geosci. Remote Sens. 43, 2684–2692 (2005).
    [CrossRef]
  17. P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
    [CrossRef] [PubMed]
  18. S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

2008

P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
[CrossRef]

2005

N. Kosaka, K. Uto, and Y. Kosugi, “ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land,” IEEE Trans. Geosci. Remote Sens. 2, 220–224 (2005).
[CrossRef]

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[CrossRef]

M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).

N. P. Jacobson and M. R. Gupta, “Design goals and solutions for display of hyperspectral images,” IEEE Trans. Geosci. Remote Sens. 43, 2684–2692 (2005).
[CrossRef]

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

2002

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[CrossRef]

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

2001

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]

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

2000

D. Scribner, P. Warren, and J. Schuler, “Extending color vision methods to bands beyond the visible,” Machine Vision Appl. 11, 306–312 (2000).
[CrossRef]

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

B.-C. Gao, M. J. Montes, Z. Ahmad, and C. O. Davis, “Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space,” Appl. Opt. 39, 887–896 (2000).
[CrossRef]

1999

J. A. Gualtieri and R. F. Cromp, “Support vector machines for hyperspectral remote sensing classification,” Proc. SPIE 3584, 221–232 (1999).
[CrossRef]

1998

Z. Lee, K. L. Carder, C. D. Mobley, R. G. Steward, and J. S. Patch, “Hyperspectral remote sensing for shallow waters. I. A semianalytical model,” Appl. Opt. 37, 6329–6338 (1998).
[CrossRef]

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

1986

A. R. Gillespie, A. B. Kahle, and R. E. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches,” Remote Sens. Environ. 20, 209–235 (1986).
[CrossRef]

Abe, T.

P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
[CrossRef]

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

Ahmad, Z.

Akiyama, T.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

Andreasen, N. C.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Arjona, M.

M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).

Bautista, P. A.

P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
[CrossRef]

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

Brettel, H.

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

Carder, K. L.

Cromp, R. F.

J. A. Gualtieri and R. F. Cromp, “Support vector machines for hyperspectral remote sensing classification,” Proc. SPIE 3584, 221–232 (1999).
[CrossRef]

Davis, C. O.

Fukuda, H.

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Gao, B.-C.

Gillespie, A. R.

A. R. Gillespie, A. B. Kahle, and R. E. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches,” Remote Sens. Environ. 20, 209–235 (1986).
[CrossRef]

Gualtieri, J. A.

J. A. Gualtieri and R. F. Cromp, “Support vector machines for hyperspectral remote sensing classification,” Proc. SPIE 3584, 221–232 (1999).
[CrossRef]

Gupta, M. R.

N. P. Jacobson and M. R. Gupta, “Design goals and solutions for display of hyperspectral images,” IEEE Trans. Geosci. Remote Sens. 43, 2684–2692 (2005).
[CrossRef]

Hardeberg, J. Y.

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

Ishida, H.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

Itano, S.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

Jacobson, N. P.

N. P. Jacobson and M. R. Gupta, “Design goals and solutions for display of hyperspectral images,” IEEE Trans. Geosci. Remote Sens. 43, 2684–2692 (2005).
[CrossRef]

Kahle, A. B.

A. R. Gillespie, A. B. Kahle, and R. E. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches,” Remote Sens. Environ. 20, 209–235 (1986).
[CrossRef]

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]

Kosaka, N.

N. Kosaka, K. Uto, and Y. Kosugi, “ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land,” IEEE Trans. Geosci. Remote Sens. 2, 220–224 (2005).
[CrossRef]

Kosugi, Y.

N. Kosaka, K. Uto, and Y. Kosugi, “ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land,” IEEE Trans. Geosci. Remote Sens. 2, 220–224 (2005).
[CrossRef]

Kruer, M.

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

Kubota, Y.

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Lee, Z.

Magnotta, V.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Martínez-Verdú, F. M.

M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).

Mitsui, M.

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[CrossRef]

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Mobley, C. D.

Montes, M. J.

Motomura, H.

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[CrossRef]

Murakami, Y.

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[CrossRef]

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[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]

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Nopoulos, P.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Obi, T.

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[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]

Ohsawa, K.

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[CrossRef]

Ohyama, N.

P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
[CrossRef]

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[CrossRef]

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[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]

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Okubo, T.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

Ooteman, W.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Patch, J. S.

Pierson, R.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Pujol, J.

M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).

Satyshur, M.

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

Schmitt, F.

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

Schuler, J.

D. Scribner, P. Warren, and J. Schuler, “Extending color vision methods to bands beyond the visible,” Machine Vision Appl. 11, 306–312 (2000).
[CrossRef]

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

Scribner, D.

D. Scribner, P. Warren, and J. Schuler, “Extending color vision methods to bands beyond the visible,” Machine Vision Appl. 11, 306–312 (2000).
[CrossRef]

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

Steward, R. G.

Teraji, T.

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[CrossRef]

Uchiyama, T.

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[CrossRef]

Uto, K.

N. Kosaka, K. Uto, and Y. Kosugi, “ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land,” IEEE Trans. Geosci. Remote Sens. 2, 220–224 (2005).
[CrossRef]

Vilaseca, M.

M. Vilaseca, J. Pujol, M. Arjona, and F. M. Martínez-Verdú, “Color visualization system for near-infrared multispectral images,” J. Imaging Sci. Technol. 49, 246–255 (2005).

Walker, R. E.

A. R. Gillespie, A. B. Kahle, and R. E. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches,” Remote Sens. Environ. 20, 209–235 (1986).
[CrossRef]

Ward, J.

J. Ward, V. Magnotta, N. C. Andreasen, W. Ooteman, P. Nopoulos, and R. Pierson, “Color enhancement of multispectral MR images: Improving the visualization of subcortical structures,” J. Comput. Assist. Tomogr. 25, 942–949 (2001).
[CrossRef] [PubMed]

Warren, P.

D. Scribner, P. Warren, and J. Schuler, “Extending color vision methods to bands beyond the visible,” Machine Vision Appl. 11, 306–312 (2000).
[CrossRef]

D. Scribner, P. Warren, J. Schuler, M. Satyshur, and M. Kruer, “Infrared color vision: an approach to sensor fusion,” Opt. Photon. News 9, 27–32 (1998).
[CrossRef]

Watanabe, N.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

Yagi, Y.

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

Yamaguchi, M.

P. A. Bautista, T. Abe, M. Yamaguchi, and N. Ohyama, “Multispectral image enhancement for H&E stained pathological tissue specimens,” Proc. SPIE 6918, 691836 (2008).
[CrossRef]

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

M. Mitsui, Y. Murakami, T. Obi, M. Yamaguchi, and N. Ohyama, “Color enhancement in multispectral image using the Karhunen-Loeve transform,” Opt. Rev. 12, 69–75 (2005).
[CrossRef]

M. Yamaguchi, T. Teraji, K. Ohsawa, T. Uchiyama, H. Motomura, Y. Murakami, and N. Ohyama, “Color image reproduction based on the multispectral and multiprimary imaging: Experimental evaluation,” Proc. SPIE 4663, 15–26 (2002).
[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]

M. Yamaguchi, M. Mitsui, Y. Murakami, H. Fukuda, N. Ohyama, and Y. Kubota, “Multispectral color imaging for dermatology: application in inflammatory and immunologic diseases,” in Proceedings of 13th Color Imaging Conference (Society for Imaging Science and Technology/Society for Information Display, 2005), pp. 52–58.

Appl. Opt.

Comput. Med. Imaging Graph.

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Comput. Med. Imaging Graph. 29, 649–657 (2005).
[CrossRef] [PubMed]

Grassland Sci.

S. Itano, T. Akiyama, H. Ishida, T. Okubo, and N. Watanabe, “Spectral characteristics of aboveground biomass, plant coverage, and plant height in Italian Ryegrass (Lolium multiflorum L.) meadows,” Grassland Sci. 46, 1–9 (2000).

IEEE Trans. Geosci. Remote Sens.

N. P. Jacobson and M. R. Gupta, “Design goals and solutions for display of hyperspectral images,” IEEE Trans. Geosci. Remote Sens. 43, 2684–2692 (2005).
[CrossRef]

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Figures (15)

Fig. 1
Fig. 1

The flow of color enhancement.

Fig. 2
Fig. 2

The multispectral image of a human skin.

Fig. 3
Fig. 3

The results of color enhancement for a skin image with the conventional method using three basis (k = 30). (a) 445 nm, (b) 545 nm, (c) 600 nm and (d) 710 nm are enhanced.

Fig. 4
Fig. 4

The flow of the color mapping method to each spectral band.

Fig. 5
Fig. 5

The results of color enhancement for a skin image with the proposed method using three basis (k = 30). (a) 445 nm, (b) 545 nm, (c) 600 nm and (d) 710 nm are enhanced.

Fig. 6
Fig. 6

The multispectral images of the liver tissue specimens. (a) The H&E stained tissue specimen. (b) The MT stained specimen of serial section.

Fig. 7
Fig. 7

Spectral data. (a) Average spectral transmittances of the fiber regions in an H&E and an MT stained liver-tissue image. (b) Average residuals of the different tissue components found in the H&E liver-tissue image. Each plot represents the average of 100 samples.

Fig. 8
Fig. 8

The enhanced results of the H&E stained tissue (n = 8,k = 30). (a) The conventional method. (b) The proposed method.

Fig. 9
Fig. 9

The enhanced results of the H&E stained tissue by automatic definition (n = 8,k = 30). (a) L * for the spectrum gd is not changed. (b) L* = 50.

Fig. 10
Fig. 10

Natural color presentation of a rice paddy image under D65 light source. The image size is 2000 × 400 pixels that was trimmed from the original image.

Fig. 11
Fig. 11

The enhanced result of the rice paddy images (k = 20). (a) 500 nm, (b) 550 nm, (c) 600 nm, (d) 650 nm, (e) 700 nm are enhanced, respectively.

Fig. 12
Fig. 12

The enhanced result of the rice paddy images (k = 20). (a) 750 nm, (b) 800 nm, (c) 850 nm, (d) 900 nm are enhanced, respectively. The weed and crop regions, which were not clearly differentiated in the original image (see Fig. 10), are now differentiated.

Fig. 13
Fig. 13

The average residual components of the different regions in the rice paddy image. Each plot represents the average of 100 samples.

Fig. 14
Fig. 14

600 × 400 pixels cropped from the magnified version of the rice paddy image enhanced at: (a) 700 nm; (b) 725 nm.

Fig. 15
Fig. 15

The average spectral reflectances of the different regions in the rice paddy image. Each plot represents the average of 100 samples.

Tables (4)

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Table 1 Center Wavelength and Bandwidth of Each Spectral Band of the Multispectral Camera

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Table 2 The Color Differences Between the Normal Skin Region and the Vein Region in Enhancing 16th Band

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Table 3 Center Wavelength and Bandwidth of Each Spectral Band of the Multispectral Camera for Microscope

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Table 4 The Color Differences Between the Cytoplasm Region and the Fiber Region

Equations (12)

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

g e j = W ( g j s j ) + g j ,
s j = i = 1 m α i j u i + g ¯ ,
α i j = u i T ( g j g ¯ ) .
[ W ] p q = { k p = q = n 0 otherwise ,
g e j = [ W ( E U U T ) + E ] g j W ( E U U T ) g ¯ ,
[ U ] q = { u q q m 0 otherwise .
[ W ] q = { k ( g d g a ) q = n 0 otherwise ,
g d = H C + [ X d Y d Z d ] ,
g = Hf .
a d * = a * ¯ , b d * = b * ¯ ,
a h * = C * cos h , b h * = C * sin h .
t ( λ ) = i ( λ ) i g ( λ ) ,

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