noise rejection
To improve the playback quality of audio and video, there are various methods that suppress noise and thus improve the signal-to-noise ratio( SNR).
The classic noise reduction methods work with frequency boosts and frequency cuts. Such noise reduction techniques can reduce the tape noise of magnetic tapes, the inherent noise of electronic components and circuits, carrier noise, and cosmic noise superimposed on the signal on the transmission path. Other methods, such as Active Noise Cancelling( ANC), compensate for ambient noise by creating interference with which the noise is cancelled out.
The classic noise cancellation methods work with frequency boosts and cuts such as emphasis or with companders and their dynamic compression and expansion of signals. All the methods used modify the signal before recording, transmission or amplification and do the opposite operation before playback, so that the original signal is reproduced without modification.
The frequency response modification procedure amplifies certain frequencies that the human ear preferentially perceives. The signal level is thus raised, improving the signal-to-noise ratio. On the receiving side, the frequency boost on the transmitting side is compensated by the opposite operation of frequency cut. This reduces the noise. The frequency response modification method is used, among other things, in VHF broadcasting with the Emphasis technique.
The compander method also works with frequency boosts, but additionally with a change in dynamics. In the compander method, the level of certain frequency ranges of the audio signals is increased more than others at the transmitting end. On the receiving end, the dynamic change is reversed. The compander method is used in Dolby.
In digital photography, temperature-dependent noise effects occur that show up as irregular colored spots. The color from the colored spots has nothing to do with the image representation. They are due to noise and increase with temperature and exposure time and are compensated for by the image signal processor to reduce the signal-to-noise ratio. This process attempts to separate the noise signal from the image information, which results in lower sharpness.