References

Aleksander, I. and Morton, H. (1991) An Introduction to Neural Computing, Chapman and Hall.

Alsam, A. and Finlayson, G.D. (2008) Integer programming for optimal reduction of calibration targets, Color Research and Application, 33 (3), 212–220.

Anton, H. (1994) Elementary Linear Algebra, John Wiley & Sons, Ltd, Chichester.

ASTM (2001) E308-01, Standard Practice for Computing the Colors of Objects by Using the CIE System.

Bala, R. (1999) Optimization of the spectral Neugebauer model for printer characterization, Journal of Electronic Imaging, 8 (2), 156–166.

Bala, R. (2003) Device Characterization, in Digital Color Imaging Handbook, G. Sharma (ed.), CRC Press.

Balasubramanian, R. and Maltz, M.S. (1996) Refinement of printer transformations using weighted regression, Proceedings of SPIE, 2658, 334–340.

Barlow, H.B. (1982) What causes trichromacy? A theoretical analysis using comb-filtered spectra, Vision Research, 22, 635–644.

Barnard, K. and Funt, B. (2002) Camera characterization for color research, Color Research and Application, 27 (3), 152–163.

Bartleson, C.J. (1978) Comparison of chromatic adaptation transforms, Color Research and Application, 3 (3), 129–136.

Bartleson, C.J. and Breneman, E.J. (1967) Brightness perception in complex fields, Journal of the Optical Society of America, 57 (7), 953–957.

Bastani, B., Cressman, B. and Funt, B. (2005) Calibrated color mapping between LCD and CRT displays: A case study, Color Research and Application, 30 (6), 438–447.

Berns, ...

Get Computational Colour Science Using MATLAB, 2nd Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.