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Understanding and Improving the Signal-To-Noise Ratio#

An ideal camera sensor would convert a known amount of light into an exactly predictable output voltage.

Unfortunately, such a sensor doesn't exist. Due to temperature conditions, electronic interference, etc., sensors will not convert light 100 % precisely. Sometimes, the output voltage will be a bit bigger than expected and sometimes, it will be a bit smaller. The difference between the ideal signal that you expect and the real-world signal that you actually see is usually called noise.

The relationship between signal and noise is called the Signal-to-Nose Ratio (SNR).

SNR is commonly expressed as a factor such as 20 to 1, 30 to 1, etc. Signal-to-noise ratio is also frequently stated in decibels (dB). The formula for calculating a signal-to-noise ratio in dB is:

SNR = 20 x log (signal / noise).

Once noise has become part of a signal, it can't be filtered or reduced. Therefore, it is best to take measures to reduce noise generation, for example:

  • Use good quality sensors and electronic devices in your camera
  • Use a good electronic architecture when designing your camera
  • Lower the temperature of the sensor and the other analog devices in your camera
  • Take measures to prevent noisy environmental conditions from influencing the signal (such as using shielded cables)

A common mistake is to increase the gain setting to improve the SNR. Since increasing gain increases both the signal and the noise, the SNR doesn't change significantly when gain is increased. Gain is not an effective tool for increasing the amount of information contained in your signal. Gain only changes the contrast of an existing image.

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