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Noise reduction is the process of removing noise from a signal. Noise reduction techniques exist for audio and images. Noise reduction algorithms may distort the signal to some degree. Noise rejection is the ability of a circuit to isolate an undesired signal component from the desired signal component, as with common-mode rejection ratio.
Almost every technique and device for signal processing has some connection to noise. Some random examples are: Noise shaping; Antenna analyzer or noise bridge, used to measure the efficiency of antennas; Noise gate; Noise generator, a circuit that produces a random electrical signal; Radio noise source used to calibrate radiotelescopes
The regularization parameter plays a critical role in the denoising process. When =, there is no smoothing and the result is the same as minimizing the sum of squares.As , however, the total variation term plays an increasingly strong role, which forces the result to have smaller total variation, at the expense of being less like the input (noisy) signal.
Example of 3 median filters of varying radiuses applied to the same noisy photograph. The median filter is a non-linear digital filtering technique, often used to remove noise from an image, [1] signal, [2] and video. [3] Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge ...
A noise squelch circuit is noise-operated and can be used in AM or FM receivers, and relies on the receiver quieting in the presence of an AM or FM carrier. To minimize the effects of voice audio on squelch operation, the audio from the receiver's detector is passed through a high-pass filter , typically passing 4,000 Hz (4kHz) and above ...
The evidence for a step is tested by statistical procedures, for example, by use of the two-sample Student's t-test. Alternatively, a nonlinear filter such as the median filter is applied to the signal. Filters such as these attempt to remove the noise whilst preserving the abrupt steps.
where is the number of bits in a quantized sample, and is the signal power calculated above. Note that for each bit added to a sample, the SQNR goes up by approximately 6 dB ( 20 × l o g 10 ( 2 ) {\displaystyle 20\times log_{10}(2)} ).
Adaptive noise cancelling is a signal processing technique that is highly effective in suppressing additive interference or noise corrupting a received target signal at the main or primary sensor in certain common situations where the interference is known and is accessible but unavoidable and where the target signal and the interference are unrelated, that is, uncorrelated [1] [2] [3].