Abstract

Performance of recently proposed multispectral imaging system for fast acquisition of two dimensional distribution of reflectance spectrum is experimentally studied. The system operation is based on a subspace vector model in which any reflectance spectrum is described in the compressed form as a linear combination of few spectral functions. A key element of the proposed system is a light source which includes a set of light-emitting diodes with different central wavelengths. The light source provides illumination of the object by fast-switchable sequences of spectral bands whose energy distributions are proportional to mutually orthogonal spectral functions (calculated in-advance). Object illumination is synchronized with a monochrome digital camera. The system allows us fast acquisition of reflectance spectra in a compressed form with high spatial resolution. A model of the system calibration by using standard white matte sample is proposed. Reconstruction of the reflectance spectrum from the compressed data collected after illumination of selected color samples from the Munsell book by 7 mutually orthogonal spectral functions is demonstrated. Parameters of the system, which affect the accuracy of the spectrum reconstruction, are analyzed and discussed.

© 2010 OSA

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    [CrossRef]

2010

2009

V. C. Paquit, K. W. Tobin, J. R. Price, and F. Mèriaudeau, “3D and multispectral imaging for subcutaneous veins detection,” Opt. Express 17(14), 11360–11365 (2009).
[CrossRef] [PubMed]

M. B. Bouchard, B. R. Chen, S. A. Burgess, and E. M. C. Hillman, “Ultra-fast multispectral optical imaging of cortical oxygenation, blood flow, and intracellular calcium dynamics,” Opt. Express 17(18), 15670–15678 (2009).
[CrossRef] [PubMed]

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

A. A. Gowen, M. Taghizadeh, and C. P. O'Donnell, “Identification of mushrooms subjected to freeze damage using hyperspectral imaging,” J. Food Eng. 93(1), 7–12 (2009).
[CrossRef]

2008

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

2007

S. C. Gebhart, R. C. Thompson, and A. Mahadevan-Jansen, “Liquid-crystal tunable filter spectral imaging for brain tumor demarcation,” Appl. Opt. 46(10), 1896–1910 (2007).
[CrossRef] [PubMed]

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

R. Lu and Y. Peng, “Development of a multispectral imaging prototype for real-time detection of apple fruit firmness,” Opt. Eng. 46(12), 123201 (2007).
[CrossRef]

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

A. A. Kamshilin and E. Nippolainen, “Chromatic discrimination by use of computer controlled set of light-emitting diodes,” Opt. Express 15(23), 15093–15100 (2007).
[CrossRef] [PubMed]

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
[CrossRef]

2005

P. Tatzer, M. Wolf, and T. Panner, “Industrial application for inline material sorting using hyperspectral imaging in the NIR range,” Real-Time Imag. 11(2), 99–107 (2005).
[CrossRef]

2003

2002

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

R. Piché, “Nonnegative color spectrum analysis filters from principal component analysis characteristic spectra,” J. Opt. Soc. Am. A 19(10), 1946–1950 (2002).
[CrossRef]

1995

N. Hayasaka, S. Toyooka, and T. Jaaskelainen, “Iterative feedback method to make a spatial filter on a liquid crystal spatial light modulator for 2D spectroscopic pattern recognition,” Opt. Commun. 119(5-6), 643–651 (1995).
[CrossRef]

1990

1989

1986

1964

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

Adibi, A.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Aleixos, N.

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

Andermann, M. L.

Attas, E. M.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Basiri, A.

Bencini, D.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Blasco, J.

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

Boas, D. A.

Bolay, H.

Bonifazzi, C.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Bouchard, M. B.

Burgess, S. A.

Carcagni, P.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Chen, B. R.

Cohen, J.

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

Comelli, D.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Conde, O. M.

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

Cubeddu, R.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Cubillas, A. M.

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

Dale, A. M.

Devor, A.

Dunn, A. K.

El-Naggar, A. K.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Ervasti, T.

Farina, A.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Fauch, L.

E. Nippolainen, T. Ervasti, L. Fauch, S. V. Miridonov, J. Ketolainen, and A. A. Kamshilin, “Fast noncontact measurements of tablet dye concentration,” Opt. Express 18(15), 15624–15634 (2010).
[CrossRef] [PubMed]

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
[CrossRef]

Fontana, R.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Gao, L.

García-Allende, P. B.

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

Gariépy, C.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

Gebhart, S. C.

Gillenwater, A. M.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Gómez, J.

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

Gowen, A. A.

A. A. Gowen, M. Taghizadeh, and C. P. O'Donnell, “Identification of mushrooms subjected to freeze damage using hyperspectral imaging,” J. Food Eng. 93(1), 7–12 (2009).
[CrossRef]

Greco, M.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Groah, S.

Guiou, M.

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

Hagen, N.

Hallikainen, J.

Hauta-Kasari, M.

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
[CrossRef]

Hayasaka, N.

N. Hayasaka, S. Toyooka, and T. Jaaskelainen, “Iterative feedback method to make a spatial filter on a liquid crystal spatial light modulator for 2D spectroscopic pattern recognition,” Opt. Commun. 119(5-6), 643–651 (1995).
[CrossRef]

Hillman, E. M. C.

Jaaskelainen, T.

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
[CrossRef]

N. Hayasaka, S. Toyooka, and T. Jaaskelainen, “Iterative feedback method to make a spatial filter on a liquid crystal spatial light modulator for 2D spectroscopic pattern recognition,” Opt. Commun. 119(5-6), 643–651 (1995).
[CrossRef]

T. Jaaskelainen, J. P. S. Parkkinen, and S. Toyooka, “Vector-subspace model for color representation,” J. Opt. Soc. Am. A 7(4), 725–730 (1990).
[CrossRef]

J. P. S. Parkkinen, J. Hallikainen, and T. Jaaskelainen, “Characteristic spectra of Munsell colors,” J. Opt. Soc. Am. A 6(2), 318–322 (1989).
[CrossRef]

Jáuregui, C.

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

Kamshilin, A. A.

Kercek, A.

R. Leitner, H. Mairer, and A. Kercek, “Real-time classification of polymers with NIR spectral imaging and blob analysis,” Real-Time Imag. 9(4), 245–251 (2003).
[CrossRef]

Kester, R. T.

Ketolainen, J.

Kong, L.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Kurachi, C.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Leitner, R.

R. Leitner, H. Mairer, and A. Kercek, “Real-time classification of polymers with NIR spectral imaging and blob analysis,” Real-Time Imag. 9(4), 245–251 (2003).
[CrossRef]

Libin, A.

Liu, F.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

López-Higuera, J. M.

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

Lu, R.

R. Lu and Y. Peng, “Development of a multispectral imaging prototype for real-time detection of apple fruit firmness,” Opt. Eng. 46(12), 123201 (2007).
[CrossRef]

Mahadevan-Jansen, A.

Mairer, H.

R. Leitner, H. Mairer, and A. Kercek, “Real-time classification of polymers with NIR spectral imaging and blob analysis,” Real-Time Imag. 9(4), 245–251 (2003).
[CrossRef]

Maloney, L. T.

Mantsch, H. H.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Mastroiani, M.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Materazzi, M.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Mathews, S.

Mèriaudeau, F.

Miridonov, S. V.

Moltó, E.

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

Moskowitz, M. A.

Nabili, M.

Nevin, A.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Ngadi, M. O.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

Nippolainen, E.

Noordmans, H. J.

O'Donnell, C. P.

A. A. Gowen, M. Taghizadeh, and C. P. O'Donnell, “Identification of mushrooms subjected to freeze damage using hyperspectral imaging,” J. Food Eng. 93(1), 7–12 (2009).
[CrossRef]

Pampaloni, E.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Panner, T.

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Parkkinen, J. P. S.

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
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[CrossRef]

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[CrossRef]

Peng, Y.

R. Lu and Y. Peng, “Development of a multispectral imaging prototype for real-time detection of apple fruit firmness,” Opt. Eng. 46(12), 123201 (2007).
[CrossRef]

Pezzati, L.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

Piché, R.

Posthumus, T. B.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Prakash, N.

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

Prasher, S. O.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
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Qiao, J.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

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Richards-Kortum, R.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

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D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Schattka, B. J.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Sheth, S. A.

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

Sokolov, K.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Sowa, M. G.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Sprigle, S.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Taghizadeh, M.

A. A. Gowen, M. Taghizadeh, and C. P. O'Donnell, “Identification of mushrooms subjected to freeze damage using hyperspectral imaging,” J. Food Eng. 93(1), 7–12 (2009).
[CrossRef]

Tatzer, P.

P. Tatzer, M. Wolf, and T. Panner, “Industrial application for inline material sorting using hyperspectral imaging in the NIR range,” Real-Time Imag. 11(2), 99–107 (2005).
[CrossRef]

Thompson, R. C.

Tkaczyk, T. S.

Tobin, K. W.

Toga, A. W.

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

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D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

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N. Hayasaka, S. Toyooka, and T. Jaaskelainen, “Iterative feedback method to make a spatial filter on a liquid crystal spatial light modulator for 2D spectroscopic pattern recognition,” Opt. Commun. 119(5-6), 643–651 (1995).
[CrossRef]

T. Jaaskelainen, J. P. S. Parkkinen, and S. Toyooka, “Vector-subspace model for color representation,” J. Opt. Soc. Am. A 7(4), 725–730 (1990).
[CrossRef]

Tummala, R.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Valentini, G.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Wang, C.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Wang, F.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Wang, N.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

Williams, M. D.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

Wolf, M.

P. Tatzer, M. Wolf, and T. Panner, “Industrial application for inline material sorting using hyperspectral imaging in the NIR range,” Real-Time Imag. 11(2), 99–107 (2005).
[CrossRef]

Yi, D.

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

Zhang, S. L.

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

Appl. Opt.

Biopolymers

E. M. Attas, M. G. Sowa, T. B. Posthumus, B. J. Schattka, H. H. Mantsch, and S. L. Zhang, “Near-IR spectroscopic imaging for skin hydration: the long and the short of it,” Biopolymers 67(2), 96–106 (2002).
[CrossRef] [PubMed]

J. Biomed. Opt.

D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” J. Biomed. Opt. 13(2), 024019 (2008).
[CrossRef] [PubMed]

L. Kong, D. Yi, S. Sprigle, F. Wang, C. Wang, F. Liu, A. Adibi, and R. Tummala, “Single sensor that outputs narrowband multispectral images,” J. Biomed. Opt. 15(1), 010502 (2010).
[CrossRef] [PubMed]

J. Food Eng.

J. Qiao, M. O. Ngadi, N. Wang, C. Gariépy, and S. O. Prasher, “Pork quality and marbling level assessment using a hyperspectral imaging system,” J. Food Eng. 83(1), 10–16 (2007).
[CrossRef]

A. A. Gowen, M. Taghizadeh, and C. P. O'Donnell, “Identification of mushrooms subjected to freeze damage using hyperspectral imaging,” J. Food Eng. 93(1), 7–12 (2009).
[CrossRef]

J. Blasco, N. Aleixos, J. Gómez, and E. Moltó, “Citrus sorting by identification of the most common defects using multispectral computer vision,” J. Food Eng. 83(3), 384–393 (2007).
[CrossRef]

J. Opt. A, Pure Appl. Opt.

C. Bonifazzi, P. Carcagni, R. Fontana, M. Greco, M. Mastroiani, M. Materazzi, E. Pampaloni, L. Pezzati, and D. Bencini, “A scanning device for VIS–NIR multispectral imaging of paintings,” J. Opt. A, Pure Appl. Opt. 10(6), 064011 (2008).
[CrossRef]

J. Opt. Soc. Am. A

Neuroimage

S. A. Sheth, N. Prakash, M. Guiou, and A. W. Toga, “Validation and visualization of two-dimensional optical spectroscopic imaging of cerebral hemodynamics,” Neuroimage 47(Suppl 2), T36–T43 (2009).
[CrossRef]

Opt. Commun.

N. Hayasaka, S. Toyooka, and T. Jaaskelainen, “Iterative feedback method to make a spatial filter on a liquid crystal spatial light modulator for 2D spectroscopic pattern recognition,” Opt. Commun. 119(5-6), 643–651 (1995).
[CrossRef]

Opt. Eng.

R. Lu and Y. Peng, “Development of a multispectral imaging prototype for real-time detection of apple fruit firmness,” Opt. Eng. 46(12), 123201 (2007).
[CrossRef]

Opt. Express

Opt. Lett.

Opt. Rev.

L. Fauch, E. Nippolainen, A. A. Kamshilin, M. Hauta-Kasari, J. P. S. Parkkinen, and T. Jaaskelainen, “Optical implementation of precise color classification using computer controlled set of light emitting diodes,” Opt. Rev. 14(4), 243–245 (2007).
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J. Cohen, “Dependency of the spectral reflectance curves of the Munsell color chips,” Psychon. Sci. 1, 369–370 (1964).

Real-Time Imag.

P. Tatzer, M. Wolf, and T. Panner, “Industrial application for inline material sorting using hyperspectral imaging in the NIR range,” Real-Time Imag. 11(2), 99–107 (2005).
[CrossRef]

R. Leitner, H. Mairer, and A. Kercek, “Real-time classification of polymers with NIR spectral imaging and blob analysis,” Real-Time Imag. 9(4), 245–251 (2003).
[CrossRef]

Rev. Sci. Instrum.

D. Comelli, G. Valentini, A. Nevin, A. Farina, L. Toniolo, and R. Cubeddu, “A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces,” Rev. Sci. Instrum. 79(8), 086112 (2008).
[CrossRef] [PubMed]

Sens. Actuators, A

P. B. García-Allende, O. M. Conde, A. M. Cubillas, C. Jáuregui, and J. M. López-Higuera, “New raw material discrimination system based on a spatial optical spectroscopy technique,” Sens. Actuators, A 135, 605–612 (2007).
[CrossRef]

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Figures (8)

Fig. 1
Fig. 1

Seven mutually orthogonal spectral functions Si (λ) calculated in Ref [25]. from the measured reflectance spectra for color samples from the Munsell book.

Fig. 2
Fig. 2

Principle scheme of the system for fast acqusition of 2D distribution of the reflectance spectra.

Fig. 3
Fig. 3

Spectral power distribution of 17 LEDs used in our light source.

Fig. 4
Fig. 4

Typical image captured by CMOS camera (white color corresponds to high irradiance) under illumination by the LED with central wavelength of 472 nm. Red circle shows the region in which the MSI system calibration and measurements of the reflection spectra were carried out.

Fig. 5
Fig. 5

Camera response as a function of the light exposure for two LEDs at the wavelength of 442 nm (squares) and 638 nm (circles) (a); Spectral dependence of the camera sensitivity (b).

Fig. 6
Fig. 6

The first (a) and second (b) spectral functions S 1(λ) and S 2(λ) as calculated theoretically (blue lines) and their implementation by the available 17 LEDs (red lines).

Fig. 7
Fig. 7

Reflectance spectrum of the standard matte white sample (black). The spectrum reconstructed using Eq. (7) with the measured coefficients σei is shown by the red solid line. Dashed blue line snows for comparison the spectrum reconstructed using Eq. (1) with theoretically calculated weighting coefficients σi .

Fig. 8
Fig. 8

Reflectance spectra of 3 color chips from the Munsell book: (a) red 5R7/8; (b) yellow 5Y7/8; and (c) blue 5B7/8. Spectra reconstructed from the measurements with our MSI system are shown by colored solid lines with dots; black solid lines represent conventionally measured spectra.

Equations (7)

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

R ( λ ) = i = 1 M [ σ i S i ( λ ) ] ,
S i ( λ ) = k N D k ( λ ) Δ t i , k .
R c ( λ ) = R N + k N D k ( λ ) C s k ( λ ) Δ t k .
S s i ( λ ) = A i k N D k ( λ ) C s k ( λ ) Δ t i , k ,
σ i = R w ( λ ) S i ( λ ) d λ .
σ s i = A i R w ( λ ) ( k N D k ( λ ) C s k ( λ ) Δ t i , k ) d λ .
R E ( λ ) = i = 1 M [ σ e i S i ( λ ) ] .

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