Image noise
Principal sources of Gaussian noise in digital images arise during acquisition.
Its effect is made worse by the distribution of silver halide grains in the film also being random.
Significant reduction of this noise can be achieved by applying notch filters in the frequency domain.
The trade-off between noise reduction and preserving fine details is application specific.
For example, if the fine details on the castle are not considered important, low pass filtering could be an appropriate option.
If the fine details of the castle are considered important, a viable solution may be to crop off the border of the image entirely.
In low light, correct exposure requires the use of slow shutter speed (i.e. long exposure time) or an opened aperture (lower f-number), or both, to increase the amount of light (photons) captured which in turn reduces the impact of shot noise.
If the limits of shutter (motion) and aperture (depth of field) have been reached and the resulting image is still not bright enough, then higher gain (ISO sensitivity) should be used to reduce read noise.
On most cameras, slower shutter speeds lead to increased salt-and-pepper noise due to photodiode leakage currents.
Any voltage fluctuations in the signal processing chain that contribute to deviation from the ideal value, proportional to the photon count, are called read noise.
The f-number is indicative of light density in the focal plane (e.g., photons per square micron).
With constant aperture diameters, the amount of light collected and the signal-to-noise ratio for shot noise are both independent of sensor size.
[23] Temperature can also have an effect on the amount of noise produced by an image sensor due to leakage.
A simplified example of the impossibility of unambiguous noise reduction: an area of uniform red in an image might have a very small black part.
This decision can be assisted by knowing the characteristics of the source image and of human vision.
Interference and static are other forms of noise, in the sense that they are unwanted, though not random, which can affect radio and television signals.
Digital noise is sometimes present on videos encoded in MPEG-2 format as a compression artifact.
It determines the amount of gain applied to the voltage output from the image sensor and has a direct effect on read noise.
All signal processing units within a digital camera system have a noise floor.
The difference between the signal level and the noise floor is called the signal-to-noise ratio.
[29] In bright sunny conditions, a slow shutter speed, wide open aperture, or some combination of all three, there can be sufficient photons hitting the image sensor to completely fill, or otherwise reach near capacity of the pixel wells.
Conversely, in darker conditions, faster shutter speeds, closed apertures, or some combination of all three, there can be a lack of sufficient photons hitting the image sensor to generate a suitable voltage from the image sensor to overcome the noise floor of the signal chain, resulting in a low signal-to-noise ratio, or high noise (predominately read noise).
