A PHOTOGRAPHER ASKS, “Why are blue skies so noisy in photos?”
A noisy blue sky in a photo, greatly enlarged.
This is a common question. Here are the issues, as far as I can tell:
Skies are blue because of the process of Rayleigh scattering, where light is diffracted around the molecules of air. The higher the frequency of light, the more it is scattered: so when you photograph a blue sky, the camera’s blue color channel will be brighter than the green, and the green will be brighter than the red channel. This also explains the orange color of sunsets — when looking directly at the sun, you are mainly seeing the light which hasn’t been scattered, which is primarily the red along with some green, giving us orange colors. On the other hand, dust and water vapor in the sky will tend to scatter all frequencies of light, desaturating the blue color given us by Rayleigh scattering. I ought to note that overcast or hazy skies do not have a noise problem.
We tend to notice noise more in uniform regions, such as blue skies. The more uniform a perception is, the more sensitive we are to subtle differences in that perception. The same absolute amount of noise in a complex, heavily textured scene will be less noticeable.
Granted that there is some noise in the sky already for whatever reason, be aware that using the common JPEG file format — which is used for most photos on the Internet — can generate additional noise due to its compression artifacts — which are blocky 8x8 pixel patterns. Again these will be more visible in areas of uniform color. The greater the compression amount, the more visible the blocky patterns. JPEG can also optionally discard more color information, leading to even more noise.
The color of a blue sky can often be close to or outside of the range or gamut of the standard sRGB and Adobe RGB color spaces — the result of this is that the red color channel will be quite dark and noisy — unless you overexpose the sky, making it a bright, textureless cyan or white. This is most obvious with brilliant, clear, and clean blue skies, such as found in winter, at high latitudes and altitudes, and when using a polarizer. At dusk, the problem is probably worse.
Depending on the camera and white balance settings, the red color channel will be amplified greatly, increasing its noise greatly, and we already know that there will likely be significant noise in the red channel already, so this just makes things worse. Also, the blue color channel might be amplified also, increasing its noise. Also consider that most cameras have double the number of green-sensitive sensels compared to the red or blue variety, leading to more noise in those color channels.
Human vision is sensitive to changes in the blue color range. Small changes in the RGB numbers in this color range are going to have a larger visual sensation than with some other colors. So a relatively small amount of noise will be more visible in the color of a blue sky.
In order to create a really clean image from a camera’s raw data, high mathematical precision in the calculations is needed, as well as the ability to accept negative or excessive values of color, temporarily, during processing, which is called “unbounded mode” calculations. Now this can make raw conversion quite slow, and so many manufacturers take shortcuts, aiming for images that are “good enough” instead of being precisely accurate. But the result of using imprecise arithmetic is extra noise, along with possibly other digital artifacts.
So the problem of blue sky noise is a nice mixture of physics, mathematics, human physiology and psychology, technical standards, and camera engineering.