Noise Reduction Techniques In Electronic Systems

Radiative coupling from radiation sources such as radio and TV broadcast stations and communication channels would not normally be considered interference sources for the low-frequency (less than 100 kHz) bandwidth measurement systems. But high-frequency noise can be rectified and introduced into low-frequency circuits through a process called audio rectification. This process results from the nonlinear junctions in ICs acting as rectifiers. Simple passive R-C lowpass filters at the receiver end of long cabling can reduce audio rectification.

Although signal processing techniques are not a substitute for proper system interconnection, they can be employed for noise reduction, as well. All noise-reducing signal processing techniques rely on trading off signal bandwidth to improve the signal-to-noise ratio. In broad terms, these can be categorized as preacquisition or postacquisition measures. Examples of preacquisition techniques are various types of filtering (lowpass, highpass, or bandpass) to reduce the out-of-band noise in the signal. The measurement bandwidth need not exceed the dynamics or the frequency range of the transducer. Postacquisition techniques can be described as digital filtering. The simplest postacquisition filtering technique is averaging. This results in comb filtering of the acquired data and is especially useful for rejecting specific interference frequencies such as 50 to 60 Hz. Remember that inductive coupling from low-frequency sources such as 50 Hz to 60 Hz power lines is harder to shield against. For optimal interference rejection by averaging, the time interval of the acquired data used for averaging, Tacq, must be an integral multiple of Trej = 1/ Frej, where Frej is the frequency being optimally rejected.

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In particular, noise is inherent in physics, and central to thermodynamics. Any conductor with electrical resistance will generate thermal noise inherently. The final elimination of thermal noise in electronics can only be achieved cryogenically, and even then quantum noise would remain inherent.

In communication systems, noise is an error or undesired random disturbance of a useful information signal in a communication channel. The noise is a summation of unwanted or disturbing energy from natural and sometimes man-made sources. Noise is, however, typically distinguished from interference,[a] for example in the signal-to-noise ratio (SNR), signal-to-interference ratio (SIR) and signal-to-noise plus interference ratio (SNIR) measures. Noise is also typically distinguished from distortion, which is an unwanted systematic alteration of the signal waveform by the communication equipment, for example in signal-to-noise and distortion ratio (SINAD) and total harmonic distortion plus noise (THD+N) measures.

Shot noise in electronic devices results from unavoidable random statistical fluctuations of the electric current when the charge carriers (such as electrons) traverse a gap. If electrons flow across a barrier, then they have discrete arrival times. Those discrete arrivals exhibit shot noise. Typically, the barrier in a diode is used.[3] Shot noise is similar to the noise created by rain falling on a tin roof. The flow of rain may be relatively constant, but the individual raindrops arrive discretely.

Flicker noise, also known as 1/f noise, is a signal or process with a frequency spectrum that falls off steadily into the higher frequencies, with a pink spectrum. It occurs in almost all electronic devices and results from a variety of effects.

While noise may be generated in the electronic circuit itself, additional noise energy can be coupled into a circuit from the external environment, by inductive coupling or capacitive coupling, or through the antenna of a radio receiver.

A noise signal is typically considered as a linear addition to a useful information signal. Typical signal quality measures involving noise are signal-to-noise ratio (SNR or S/N), signal-to-quantization noise ratio (SQNR) in analog-to-digital conversion and compression, peak signal-to-noise ratio (PSNR) in image and video coding and noise figure in cascaded amplifiers. In a carrier-modulated passband analogue communication system, a certain carrier-to-noise ratio (CNR) at the radio receiver input would result in a certain signal-to-noise ratio in the detected message signal. In a digital communications system, a certain Eb/N0 (normalized signal-to-noise ratio) would result in a certain bit error rate. Telecommunication systems strive to increase the ratio of signal level to noise level in order to effectively transfer data. Noise in telecommunication systems is a product of both internal and external sources to the system.

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.

In electronic systems, a major type of noise is hiss created by random electron motion due to thermal agitation. These agitated electrons rapidly add and subtract from the output signal and thus create detectable noise.

Four types of noise reduction exist: single-ended pre-recording, single-ended hiss reduction, single-ended surface noise reduction, and codec or dual-ended systems. Single-ended pre-recording systems (such as Dolby HX Pro), work to affect the recording medium at the time of recording. Single-ended hiss reduction systems (such as DNL[11] or DNR) work to reduce noise as it occurs, including both before and after the recording process as well as for live broadcast applications. Single-ended surface noise reduction (such as CEDAR and the earlier SAE 5000A, Burwen TNE 7000, and Packburn 101/323/323A/323AA and 325[12]) is applied to the playback of phonograph records to address scratches, pops, and surface non-linearities. Single-ended dynamic range expanders like the Phase Linear Autocorrelator Noise Reduction and Dynamic Range Recovery System (Models 1000 and 4000) can reduce various noise from old recordings. Dual-ended systems (such as Dolby noise-reduction system or dbx) have a pre-emphasis process applied during recording and then a de-emphasis process applied at playback.

The first widely used audio noise reduction technique was developed by Ray Dolby in 1966. Intended for professional use, Dolby Type A was an encode/decode system in which the amplitude of frequencies in four bands was increased during recording (encoding), then decreased proportionately during playback (decoding). In particular, when recording quiet parts of an audio signal, the frequencies above 1 kHz would be boosted. This had the effect of increasing the signal-to-noise ratio on tape up to 10 dB depending on the initial signal volume. When it was played back, the decoder reversed the process, in effect reducing the noise level by up to 10 dB.

dbx was a competing analog noise reduction system developed by David E. Blackmer, founder of Dbx, Inc..[22] It used a root-mean-squared (RMS) encode/decode algorithm with the noise-prone high frequencies boosted, and the entire signal fed through a 2:1 compander. dbx operated across the entire audible bandwidth and unlike Dolby B was unusable without a decoder. However, it could achieve up to 30 dB of noise reduction.

Since analog video recordings use frequency modulation for the luminance part (composite video signal in direct color systems), which keeps the tape at saturation level, audio-style noise reduction is unnecessary.

It was further developed into dynamic noise reduction (DNR) by National Semiconductor to reduce noise levels on long-distance telephony.[25] First sold in 1981, DNR is frequently confused with the far more common Dolby noise-reduction system.[26]

Unlike Dolby and dbx Type I and Type II noise reduction systems, DNL and DNR are playback-only signal processing systems that do not require the source material to first be encoded. They can be used to remove background noise from any audio signal, including magnetic tape recordings and FM radio broadcasts, reducing noise by as much as 10 dB.[27] They can also be used in conjunction with other noise reduction systems, provided that they are used prior to applying DNR to prevent DNR from causing the other noise reduction system to mistrack.[28]

One of DNR's first widespread applications was in the GM Delco car stereo systems in US GM cars introduced in 1984.[29] It was also used in factory car stereos in Jeep vehicles in the 1980s, such as the Cherokee XJ. Today, DNR, DNL, and similar systems are most commonly encountered as a noise reduction system in microphone systems.[30]

Modern digital sound (and picture) recordings no longer need to worry about tape hiss so analog style noise reduction systems are not necessary. However, an interesting twist is that dither systems actually add noise to a signal to improve its quality.

In real-world photographs, the highest spatial-frequency detail consists mostly of variations in brightness ("luminance detail") rather than variations in hue ("chroma detail"). Since any noise reduction algorithm should attempt to remove noise without sacrificing real detail from the scene photographed, one risks a greater loss of detail from luminance noise reduction than chroma noise reduction simply because most scenes have little high frequency chroma detail to begin with. In addition, most people find chroma noise in images more objectionable than luminance noise; the colored blobs are considered "digital-looking" and unnatural, compared to the grainy appearance of luminance noise that some compare to film grain. For these two reasons, most photographic noise reduction algorithms split the image detail into chroma and luminance components and apply more noise reduction to the former.

Smoothing filters tend to blur an image, because pixel intensity values that are significantly higher or lower than the surrounding neighborhood would "smear" across the area. Because of this blurring, linear filters are seldom used in practice for noise reduction; they are, however, often used as the basis for nonlinear noise reduction filters.

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