Hideyasu Kuniba

Spectral sensitivity optimization of color image sensors considering photon shot noise

Filter optimization is investigated to design digital camera color filters that achieved high color accuracy and low image noise when a sensors 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.

Spectral sensitivity optimization of color image sensor considering photon shot noise

A filter optimization was investigated to design digital camera color filters that achieved high color accuracy and low image noise when accounting for a sensors 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.

Spectral sensitivity optimization of color image sensors considering photon shot noise: four-channel sensor models

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.