Digital cameras are used under a wide spectrum of illuminants and should adjust the white point according to the
illuminant used (white balance correction). The white balance correction makes "white" object be reproduced
as "white" but the reproduction of chromatic objects will not necessarily be appropriate (color constancy error).
Three types of sensor models were used for the simulation. The error was reduced by a primary conversion
that made overlaps and widths of the channels smaller. Thus two new metrics that evaluated the overlaps and
the widths were defined and used to optimize the conversion to a color space suitable for white-balancing and
it was shown that the color constancy errors were reduced. It was also shown that the color constancy error
was small for the sensor model whose overlaps between channels were small and channel widths were narrow.
The narrower widths and smaller overlaps of RGB channels gave less accurate colorimetric reproduction but less
noisy images. In view of consumer digital cameras, the narrower widths and smaller overlaps of RGB channels
is suitable because it can give less noisy images and consistent color reproduction with simple white balance
Four channel sensors were evaluated with a image sensor model and their performance was compared with
three channel sensors considering both color reproduction accuracy and photo shot noise. When noise was not
considered, a sensor with usual RGB plus an additional channel which resided between G and B was the best.
But when the emphasis was on noise, a sensor with B, R and two Gs was the best because reducing noise of
G should be effective in reducing noise of all L*a*b* components. Bayer color filter array (CFA) samples twice
density of G than R or B. This CFA is considered to be efficient in resolution but the result suggests it is also
efficient in SNR. Comparing to three channel sensors, the four channel sensors were better in color reproduction
but worse in noise. An image preference model proposed by Kuniba and Berns was used to evaluate them and
it was shown that neither one was superior than the other.
KEYWORDS: RGB color model, Optical filters, Interference (communication), Color reproduction, Sensors, Color image segmentation, Image sensors, Signal to noise ratio, Quantum efficiency, Image filtering
Filter optimization is investigated to design digital camera color filters that achieved high color accuracy and low image noise when a sensor's inherent photon shot noise is considered. In a computer simulation, both RGB- and CMY-type filter sets are examined. Although CMY filters collect more photons, performance is worse than for RGB filters in terms of either color reproduction or noise due to the large noise amplification during the color transformation. When RGB filter sets are used and photon shot noise is considered, the peak wavelength of the R channel should be longer (620 to 630 nm) than the case when only color reproduction is considered: peak wavelengths 600, 550, and 450 nm for RGB channels, respectively. Increasing the wavelength reduces noise fluctuation along the a* axis, the most prominent noise component in the latter case; however, color accuracy is reduced. The tradeoff between image noise and color accuracy due to the peak wavelength of the R channel leads to a four-channel camera consisting of two R sensors and G and B. One of the two R channels is selected according to the difference in levels to reduce noise while maintaining accurate color reproduction.
A filter optimization was investigated to design digital camera color filters that achieved high color accuracy and low image noise when accounting for a sensor's inherent photon shot noise. In the computer simulation, Gaussiantype spectral-sensitivity curves along with an IR blocking filter were used. When only color reproduction was considered, the best peak wavelengths for RGB channels were 600, 550 and 450nm, respectively, but when both color reproduction and photon shot noise were considered, the peak wavelength of the R channel should be longer (620 - 630nm). Increasing the wavelength reduced noise fluctuation along the a* axis, the most prominent noise component in the former case; however, color accuracy was reduced. The tradeoff between image noise and color accuracy due to the peak wavelength of the R channel led to a four-channel camera consisting of two R sensors and G and B. One of the two R channels was selected according to the difference in levels in order to reduce noise while maintaining accurate color reproduction.