Why aren’t RGBW or red-blue-neutral Bayer-style sensor filters common?
Asked 8/5/2015
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Standard Bayer sensors use red, green, and blue color filters over the pixel array. Since each filter blocks part of the spectrum, I wondered why a sensor design with red, blue, and an unfiltered/neutral (white) pixel isn’t more common.
In that scheme, the neutral pixel would collect more light, and green could be inferred approximately as neutral minus red minus blue. In theory this might improve sensitivity compared with RGB, at the cost of more processing.
What are the main technical reasons this kind of RGBW / red-blue-neutral mosaic is not commonly used in cameras?
Originally by Photography Stack Exchange contributor. Source · Licensed CC BY-SA 4.0
Photography Stack Exchange contributor
11y ago
2 Answers
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Due to overlap between the responses of the Bayer filter dyes it's closer to 50% light loss (one stop) than two thirds.
Your scheme would work but at the expense of colour accuracy and colour resolution (the demosaicing process would be less constrained and more error prone). Combined with the fact the sensitivity gain is rather modest (up to 25% depending on the layout), this explains the prevalence of RGB Bayer sensors.
A better approach would probably be to widen the response of all dyes so you get a CMY sensor. However the same drawbacks apply and you still don't gain much in terms of sensitivity.
Originally by user1375. Source · Licensed CC BY-SA 4.0
user1375
11y ago
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The main tradeoff is that the sensitivity gain is modest, while the penalties in color accuracy and reconstruction are significant.
A Bayer sensor does not lose as much light as “2/3” in practice; because filter responses overlap, the loss is closer to about one stop. So an RGBW-style design would not gain a dramatic amount of sensitivity.
The bigger issue is color quality. Camera color is reconstructed by mixing all sensor channels, and a white/neutral pixel is spectrally broad, making the demosaicing and color-matrix conversion less constrained and more error-prone. Inferring green as neutral minus red minus blue amplifies noise and increases color error. It can also reduce color resolution and make edge artifacts worse when adjacent pixels see different colors.
There are also engineering costs: the neutral pixel would receive much more light than the filtered ones, so matching channel behavior and processing becomes harder.
Related alternatives such as CMY or RGBW mosaics have been explored, but Bayer RGB has remained dominant because it is accurate, practical, and “good enough” compared with the relatively small sensitivity benefit of broader or unfiltered channels.
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AI11y ago
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