Abstract

The development of color pixels in modern digital imaging has led to devices in which color detection is not based on the use of physical color filters but relies on the wavelength dependence of the silicon absorption coefficient in the visible range. In some of these devices the responsivity of each color channel can be electrically tuned by changing the applied voltages. Exploiting this feature, this paper presents a new method of white balance that compensates for changes in the illuminant spectrum by changing accordingly the spectral responsivities, and therefore the native color space, of the detector. Different sets of responsivities corresponding to the different RGB color channels can be selected, depending on the illuminant, in order to keep the chromatic components of a white object independent of the illuminant. An implementation of this method with the transverse field detector, a color device with tunable spectral responsivities, is discussed. Experimental data show that the method is effective for three spectral sources that are strongly different from a chosen reference source. The color error in a perceptive color space after the subsequent color correction (specific for each set of base filters) does not change significantly in the tuning interval of interest for image acquisition.

© 2009 Optical Society of America

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References

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    [CrossRef]
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    [CrossRef] [PubMed]
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    [CrossRef]
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    [CrossRef]
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  10. S. Quan, “Evaluation and optimal design of spectral sensitivities for digital color imaging,” Ph.D. thesis (Rochester Institute of Technology, 2002).
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    [CrossRef]
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    [CrossRef]
  17. A. Longoni, F. Zaraga, and G. Langfelder, “Luminous radiation color photosensitive structure,” Italian Patent MI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]

2009 (2)

G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectral responses in a color sensitive CMOS pixel for imaging applications,” IEEE Trans. Electron Devices 56, 2563-2569 (2009).
[CrossRef]

G. Langfelder, “Isolation of highly doped junctions in low-doped active layers for CMOS radiation detectors,” IEEE Trans. Electron Devices 56, 1767-1773 (2009).
[CrossRef]

2008 (1)

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

2005 (1)

A. El Gamal and H. Eltoukhy, “CMOS image sensors,” IEEE Circuits Devices Mag. May-June, pp. 6-20, 2005.
[CrossRef]

2004 (3)

D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time color imaging with a CMOS sensor having stacked photodiodes,” Proc. SPIE 5210, 105-115 (2004).
[CrossRef]

F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recogn. 37, 1201-1217 (2004).
[CrossRef]

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

2003 (1)

B. Funt and H. Jiang, “Non-von-Kries 3 parameter color prediction,” Proc. SPIE 5007, 182-189 (2003).
[CrossRef]

1999 (1)

D. X. D. Yang and A. El Gamal, “Comparative analysis of SNR for image sensors with enhanced dynamic range,” Proc. SPIE 3649, 197-211 (1999).
[CrossRef]

1994 (2)

1993 (1)

1956 (1)

1933 (1)

Bayer, B. E.

B. E. Bayer, “Color imaging array,” U.S. Patent 3,971,065, July 20, 1976.

Bianco, S.

S. Bianco, F. Gasparini, and R. Schettini, “Combining strategies for automatic white estimation in real images,” in Proceedings of 14th International Conference on Image Analysis and Processing Workshops (ICIAPW, 2007), pp. 175-178.

Bombelli, L.

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

Catrysse, P. B.

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

Chen, H.

C. Weng, H. Chen, and C. Fuh, “A novel automatic white balance method for digital still cameras,” in Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS) (IEEE, 2005), pp. 3801-3804.

Chong, H. Y.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 2007), pp. 1-8.

Drew, M.

Drew, M. S.

El Gamal, A.

A. El Gamal and H. Eltoukhy, “CMOS image sensors,” IEEE Circuits Devices Mag. May-June, pp. 6-20, 2005.
[CrossRef]

D. X. D. Yang and A. El Gamal, “Comparative analysis of SNR for image sensors with enhanced dynamic range,” Proc. SPIE 3649, 197-211 (1999).
[CrossRef]

Eltoukhy, H.

A. El Gamal and H. Eltoukhy, “CMOS image sensors,” IEEE Circuits Devices Mag. May-June, pp. 6-20, 2005.
[CrossRef]

Farrell, J. E.

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

Finlayson, G. D.

Fuh, C.

C. Weng, H. Chen, and C. Fuh, “A novel automatic white balance method for digital still cameras,” in Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS) (IEEE, 2005), pp. 3801-3804.

Funt, B.

Funt, B. V.

Gage, H. P.

Gasparini, F.

F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recogn. 37, 1201-1217 (2004).
[CrossRef]

S. Bianco, F. Gasparini, and R. Schettini, “Combining strategies for automatic white estimation in real images,” in Proceedings of 14th International Conference on Image Analysis and Processing Workshops (ICIAPW, 2007), pp. 175-178.

Gilblom, D. L.

D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time color imaging with a CMOS sensor having stacked photodiodes,” Proc. SPIE 5210, 105-115 (2004).
[CrossRef]

Gortler, S. J.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 2007), pp. 1-8.

Hirakawa, K.

K. Hirakawa and T. W. Parks, “Chromatic adaptation and white-balance problem,” in Proceedings of the International Conference on Image Processing (ICIP, 2005), pp. 984-987.

Jiang, H.

B. Funt and H. Jiang, “Non-von-Kries 3 parameter color prediction,” Proc. SPIE 5007, 182-189 (2003).
[CrossRef]

Langfelder, G.

G. Langfelder, “Isolation of highly doped junctions in low-doped active layers for CMOS radiation detectors,” IEEE Trans. Electron Devices 56, 1767-1773 (2009).
[CrossRef]

G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectral responses in a color sensitive CMOS pixel for imaging applications,” IEEE Trans. Electron Devices 56, 2563-2569 (2009).
[CrossRef]

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

F. Zaraga and G. Langfelder, “Foto-rivelatore e metodo per rivelare una radiazione ottica,” Italian Patent MI2009A000500 (2009).

A. Longoni, F. Zaraga, and G. Langfelder, “Luminous radiation color photosensitive structure,” Italian Patent MI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.

Longoni, A.

G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectral responses in a color sensitive CMOS pixel for imaging applications,” IEEE Trans. Electron Devices 56, 2563-2569 (2009).
[CrossRef]

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

A. Longoni, F. Zaraga, and G. Langfelder, “Luminous radiation color photosensitive structure,” Italian Patent MI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.

MacAdam, D. L.

Merrill, R. B.

R. B. Merrill (Foveon Inc.), “Color separation in an active pixel cell imaging array using a triple-well structure,” U.S. Patent 5,965,875, October 12, 1999.

Parks, T. W.

K. Hirakawa and T. W. Parks, “Chromatic adaptation and white-balance problem,” in Proceedings of the International Conference on Image Processing (ICIP, 2005), pp. 984-987.

Quan, S.

S. Quan, “Evaluation and optimal design of spectral sensitivities for digital color imaging,” Ph.D. thesis (Rochester Institute of Technology, 2002).

Schettini, R.

F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recogn. 37, 1201-1217 (2004).
[CrossRef]

S. Bianco, F. Gasparini, and R. Schettini, “Combining strategies for automatic white estimation in real images,” in Proceedings of 14th International Conference on Image Analysis and Processing Workshops (ICIAPW, 2007), pp. 175-178.

Silverstein, L. D.

B. A. Wandell and L. D. Silverstein, “Digital color reproduction,” in The Science of Color (Elsevier, 2003), pp. 281-316.
[CrossRef]

Stiles, W. S.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

Trussel, H. J.

Ventura, P.

D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time color imaging with a CMOS sensor having stacked photodiodes,” Proc. SPIE 5210, 105-115 (2004).
[CrossRef]

Vora, P. L.

Wandell, B. A.

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

B. A. Wandell, “Color appearance and the digital imaging pipeline,” in Proceedings of the 15th International Conference on Pattern Recognition (ICPR, 2000), Vol. 1, pp. 183-190.
[CrossRef]

B. A. Wandell and L. D. Silverstein, “Digital color reproduction,” in The Science of Color (Elsevier, 2003), pp. 281-316.
[CrossRef]

Weng, C.

C. Weng, H. Chen, and C. Fuh, “A novel automatic white balance method for digital still cameras,” in Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS) (IEEE, 2005), pp. 3801-3804.

Wyszecki, G.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

Xiao, F.

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

Yang, D. X. D.

D. X. D. Yang and A. El Gamal, “Comparative analysis of SNR for image sensors with enhanced dynamic range,” Proc. SPIE 3649, 197-211 (1999).
[CrossRef]

Yoo, S. K.

D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time color imaging with a CMOS sensor having stacked photodiodes,” Proc. SPIE 5210, 105-115 (2004).
[CrossRef]

Zaraga, F.

G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectral responses in a color sensitive CMOS pixel for imaging applications,” IEEE Trans. Electron Devices 56, 2563-2569 (2009).
[CrossRef]

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

F. Zaraga and G. Langfelder, “Foto-rivelatore e metodo per rivelare una radiazione ottica,” Italian Patent MI2009A000500 (2009).

A. Longoni, F. Zaraga, and G. Langfelder, “Luminous radiation color photosensitive structure,” Italian Patent MI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.

Zickler, T.

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 2007), pp. 1-8.

IEEE Circuits Devices Mag. (1)

A. El Gamal and H. Eltoukhy, “CMOS image sensors,” IEEE Circuits Devices Mag. May-June, pp. 6-20, 2005.
[CrossRef]

IEEE Electron Device Lett. (1)

A. Longoni, F. Zaraga, G. Langfelder, and L. Bombelli, “The transverse field detector: a novel color sensitive CMOS Device,” IEEE Electron Device Lett. 29, 1306-1308 (2008).
[CrossRef]

IEEE Trans. Electron Devices (2)

G. Langfelder, F. Zaraga, and A. Longoni, “Tunable spectral responses in a color sensitive CMOS pixel for imaging applications,” IEEE Trans. Electron Devices 56, 2563-2569 (2009).
[CrossRef]

G. Langfelder, “Isolation of highly doped junctions in low-doped active layers for CMOS radiation detectors,” IEEE Trans. Electron Devices 56, 1767-1773 (2009).
[CrossRef]

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (3)

Pattern Recogn. (1)

F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recogn. 37, 1201-1217 (2004).
[CrossRef]

Proc. SPIE (4)

B. Funt and H. Jiang, “Non-von-Kries 3 parameter color prediction,” Proc. SPIE 5007, 182-189 (2003).
[CrossRef]

D. L. Gilblom, S. K. Yoo, and P. Ventura, “Real-time color imaging with a CMOS sensor having stacked photodiodes,” Proc. SPIE 5210, 105-115 (2004).
[CrossRef]

D. X. D. Yang and A. El Gamal, “Comparative analysis of SNR for image sensors with enhanced dynamic range,” Proc. SPIE 3649, 197-211 (1999).
[CrossRef]

J. E. Farrell, F. Xiao, P. B. Catrysse, and B. A. Wandell, “A simulation tool for evaluating digital camera image quality, image quality and system performance,” Proc. SPIE 5294, 124-131 (2004).
[CrossRef]

Other (13)

S. Bianco, F. Gasparini, and R. Schettini, “Combining strategies for automatic white estimation in real images,” in Proceedings of 14th International Conference on Image Analysis and Processing Workshops (ICIAPW, 2007), pp. 175-178.

B. A. Wandell and L. D. Silverstein, “Digital color reproduction,” in The Science of Color (Elsevier, 2003), pp. 281-316.
[CrossRef]

B. A. Wandell, “Color appearance and the digital imaging pipeline,” in Proceedings of the 15th International Conference on Pattern Recognition (ICPR, 2000), Vol. 1, pp. 183-190.
[CrossRef]

Image System Evaluation Toolbox--ISET 2.0 User Manual, ImagEval Consulting.

F. Zaraga and G. Langfelder, “Foto-rivelatore e metodo per rivelare una radiazione ottica,” Italian Patent MI2009A000500 (2009).

B. E. Bayer, “Color imaging array,” U.S. Patent 3,971,065, July 20, 1976.

A. Longoni, F. Zaraga, and G. Langfelder, “Luminous radiation color photosensitive structure,” Italian Patent MI2006A002352 (2006); International Patent Appl. PCT/IB2007/003906.

R. B. Merrill (Foveon Inc.), “Color separation in an active pixel cell imaging array using a triple-well structure,” U.S. Patent 5,965,875, October 12, 1999.

C. Weng, H. Chen, and C. Fuh, “A novel automatic white balance method for digital still cameras,” in Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS) (IEEE, 2005), pp. 3801-3804.

K. Hirakawa and T. W. Parks, “Chromatic adaptation and white-balance problem,” in Proceedings of the International Conference on Image Processing (ICIP, 2005), pp. 984-987.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, 1982).

S. Quan, “Evaluation and optimal design of spectral sensitivities for digital color imaging,” Ph.D. thesis (Rochester Institute of Technology, 2002).

H. Y. Chong, S. J. Gortler, and T. Zickler, “The von Kries hypothesis and a basis for color constancy,” in Proceedings of the IEEE International Conference on Computer Vision (IEEE, 2007), pp. 1-8.

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Figures (6)

Fig. 1
Fig. 1

Examples of color pixels with tunable spectral responses: (a) A 3-color device built through stacked junctions [14, 15]. The photoresponse of the n th junction may be varied by changing the extent of its depleted region d n . (b) Isopotential lines in the active layer of the TFD [16, 17, 18]. This device has a sole depleted region. In a large part of this region a suitable electric field configuration drives carriers generated at different depths to different surface electrodes. In the scheme the arrows represent the trajectories of three carriers generated at different depths. A different electric field configuration can lead to different collection trajectories.

Fig. 2
Fig. 2

Simplified scheme of a photographic apparatus for digital imaging: the white balance is usually performed in the analog or digital section. In the present work it is instead performed by means of a tuning of the sensor responsivities (TSR) inside the sensor.

Fig. 3
Fig. 3

Spectral radiance of four common but strongly different sources: the standard D65, simulating the daylight on a sunny day (solid curve); the standard A, simulating a tungsten bulb at 2856 K (dotted curve); the standard D75, simulating a daylight at northern latitudes (dashed curve); a fluorescent lamp (dashed–dotted curve). All the radiances are taken from the ISET software and are cut off at the ends of the visible spectrum by means of a UV and an IR filter.

Fig. 4
Fig. 4

Experimental spectral sensitivities of the TFD RGB electrodes [(a), (b), (c), respectively] used in this work. Solid curves show the filters tuned for the D65 source, the dotted curves those tuned for the A source, the dashed curves those for the D75 source, and the dashed–dotted lines those for the fluorescent lamp. The particular CMOS process used in this work has an unavoidable step of deposition on top of the detector of several protective layers, which do not transmit evenly the incoming light. This is the reason for the jagged behavior of the spectral responsivity curves.

Fig. 5
Fig. 5

xy representation of the colors of a Gretag Macbeth checker illuminated by a D65 source as measured by the TFD with spectral sensitivities equal to the solid curves of Fig. 4 transformed with the CCM M 1 (circles). The error bars lead to the original color points.

Fig. 6
Fig. 6

Points representing the color of a perfect diffuser obtained in the different situations described in the box. The circles refer to an illumination through the D65 source and to the spectral sensitivities tuned for the D65 source (depicted by solid curves in Fig. 4) after the color conversion through M 1 . The x marker refers to the same sensitivities set, but to an illumination obtained from a different source [the A source in (a), the D75 source in (b), and the fluorescent source in (c)]. The square quantitatively represents the effect of the TSR-WB algorithm. The final points after the new color correction through a new, suitable CCM are represented by the plus sign.

Tables (1)

Tables Icon

Table 1 Summary of the Experimental Results

Equations (16)

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

i n = λ min λ max L ( λ ) r ( λ ) f n ( λ ) d ( λ ) d λ ,
v n = i n t int C .
σ n = 2 q ( i n + i d ) t int + σ fixed 2 C ,
i b = λ min λ max L A ( λ ) f b ( λ ) d ( λ ) d λ ,
i g = λ min λ max L A ( λ ) f g ( λ ) d ( λ ) d λ ,
i r = λ min λ max L A ( λ ) f r ( λ ) d ( λ ) d λ .
v b = i b k b t int C b ,
v g = i g k g t int C g ,
v r = i r k r t int C r ,
v b = v g = v r .
SNR b = i b t int 2 q ( i b + i d ) t int + σ fixed 2 .
i b = λ min λ max L A ( λ ) f b ( λ ) d ( λ ) d λ ,
i g = λ min λ max L A ( λ ) f g ( λ ) d ( λ ) d λ ,
i r = λ min λ max L A ( λ ) f r ( λ ) d ( λ ) d λ .
SNR b = i b t int 2 q ( i b + i d ) t int + σ fixed 2 ,
M 1 = [ 2.025 4.632 1.898 1.036 8.816 4.757 0.517 3.799 3.516 ] .

Metrics