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It is widely observed that the blue channel in digital cameras is the noisiest. I've certainly noticed that with my camera. Why is this?
Is it an artifact of some particular technology (e.g. Bayer array or CMOS sensors), or is something to do with the physics of higher-frequency light, or is it related to human vision?
Followup question: Why are sensors less sensitive to blue light?
In addition to the sensor response discussed by Tall Jeff, most scene illumination (sunlight, incandescent) is deficient in blue light relative to green and red. Fire up this Java blackbody simulator and see that blue is lower than green or red for color temperatures of interest (~5500 K daylight, ~3000 K incandescent).
There's another small factor that compounds the problem. CCD and CMOS arrays are photon-counting detectors. Most plots, including those in the blackbody simulator above, show spectral energy density, not photon counts. Blue photons are more energetic than red photons, by the inverse ratio of their wavelengths, so for the same energy value on the plots, you would get about 25% more red photons than blue photons. And that's the starting point for the sensitivity effects Tall Jeff describes.
Regarding CCDs and backside-illuminated sensors, frontside-illuminated CCDs do suffer from the same diminished blue sensitivity, as much of the blue light is absorbed while passing through the non-sensitive gate structure of the chip. Backside-illuminated sensors will see an improved blue response. See this typical spectral response curve (for various types of research-grade CCDs).
Given the current state of the art, the noise in the blue channel is a combination of cascading effects that work together to make the blue "look" the worst. First, with the Bayer pattern setup, there are twice as many green pixels as red or blue ones in the matrix*. This immediately puts the blue and red at a spacial disadvantage as compared to the green channel and results in much more spectral noise for those two channels when the RGB triplets are reconstructed from adjacent sensor pixels. For example, a 10M pixel sensor is going to have 5M source green pixels, 2.5M red ones and 2.5M blue ones. Clearly, when you form that raw information into the final 10M RGB triplets, it's clear that there can be no better than 1/2 as much information for red or blue channel and this appears as a form of noise in the final image.
The next effect has to do with the spectral sensitivities of the sensor system through the Red, Green and Blue filters. As a system, modern CMOS sensors are about 50% more sensitive to the Green and Red areas of the spectrum than they are to the blue areas. For example, for this CMOS sensor from Cypress, we can see on Page 3 that the relative sensitivities are about Red (75%), Green (80%), Blue (50%) when you index the curves at the right wavelengths for each color. This lack of sensitivity combined with a fixed level of sensor and sampling noise for all pixels across the sensors put blue at a significant signal to noise ratio disadvantage as compared to the other two colors.
Netting this out, this means that color CMOS sensors are doing the best at reproducing Green, followed second by Red, and finally by Blue which is the worst of three from an overall noise perspective.
Looking toward the future, note that these limitations with the blue channel are really mostly a matter of a cost/performance optimization. That is, there is nothing inherent to physics that requires blue performance to be worse, only that it would be MUCH MUCH more expensive given current device constructions to improve the blue channel by a noticeable margin. Also, given that the human eye is not very sensitive on the blue/yellow color axis the solutions are already a very well optimized solution. In fact, I'm sure most camera makers would prefer total cost to drop first before paying the same or more just to improve blue channel noise performance.
**Bayer chose to setup the matrix this way because the human visual system gets the majority of it's luminance signal (ie: brightness information) from the green part of the color spectrum. That is, the rods in the eyes are most sensitive to green light making the green part of the spectrum the most important visually.*
Because human eyes/brains are not as sensitive to changes in blue light as they are to changes in green/red lights. The modern camera sensors acts more like human eyes and therefore its less sensitive to blue than it is to green/red. Since the standard for displaying neutral on color monitors is to have equal amounts of blue, green, and red, and since the sensors are less sensitive to blue than to red and green, it is convenient to amplify the blue channel. Amplifying the blue channel signal also amplifies blue channel noise.
Camera noise reduction is only applied if you're shooting JPEG but since a lot of people shoot RAW, the blue channel is always somewhat noisy. I've searched for a remedy to this problem. One suggested to convert the image to lab color and smooth/blur only the luminance channel, then convert back to RGB to remove noise. You can try.
We have done an analysis of the blue-green-red channels of a DP3 Merrill in digital (RAW) mode. I just purchased this camera in June, 2018. The blue channel exhibits a level dependent error in the a/d converter that is not present in the red-green channels, which function as expected. It appears that there may be an error in either wiring the blue channel a/d or in the code which translates the a/d voltage to the blue channel digital signal. It is NOT a sensitivity issue. It could be a saturation issue, i.e. physical voltages are exceeding the a/d range at very low voltages, i.e. too much gain in that channel. The camera was set at ISO 100 for acquiring data, and data were acquired over a range of shutter speeds and signal levels over a frame. The blue channel measurements were most nearly correct signals at the LOWEST signal levels. The higher the signal, the greater the error. It is a gain/digitization problem in the algorithm producing the X3F files, or perhaps a byte ordering problem. We are looking at the X3F files directly to see if the error is already present there, but I expect it is since both the TIFF and JPEG files produced by the converter have the same issue. It is a question if the manufacturer will be interested to correct this problem? The Foveon chip is a good idea that needs to be engineered properly.
