CEDAR Duo – declickle and auto dehiss
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An
Expander
is another device with a threshold control, but unlike the gate, this applies a
progressive gain reduction, the amount of which is determined by the user. For example, if a
signal drops 3dB below the threshold, the Expander may reduce the signal volume by 6dB,
12dB, or any other figure, depending upon the expansion ratio. Unfortunately, the subjective
difference between the gate and the expander is small.
A
Multi-band Expander
separates the audio spectrum into a number of bands, treating each
as an individual signal. But multi-band units are still unable to distinguish accurately between
genuine signal and noise. They still act upon the inaccurate assumption that, if the total signal
level approaches its noise floor, all that is present is noise.
Consequently, even the most sophisticated expanders remove genuine signal. Furthermore, the
poor band separation filters (typically -6dB/oct or -12dB/oct) severely limit performance. The
consequences of these problems are loss of high frequencies, loss of ambience, and degradation
of hard transients. Some units feature a combination of dynamic filtering, expansion, and even
compression and excitation - effects which have been included in order to obscure some of the
side-effects of the noise reduction processes. But these are only partially successful.
All the processes so far described are 'ratio' operations - that is, if (at any given frequency) you
remove half the noise, you remove half the signal; if you remove 3/4 of the noise, you remove
3/4 of the signal... and so on. Consider now a signal that has, at a given frequency, 100 units of
'volume' on an arbitrary scale. By measuring the noise content of that signal during an
otherwise silent passage, you can determine that there are, say, 20 units of noise present at
that frequency. It should be possible to remove this noise by removing 20% of the signal. But
what if, a moment later, the total 'volume' of the signal drops to 40 units? An analogue filter,
removing 20% of the signal, will remove 8 units. On the other hand, a subtractive filter (which
is practical only in the digital domain) will still remove the full 20 units - a reduction of 50%.
This is what we want, because the noise at this moment represents 50% of the total signal.
This
Spectral Subtraction
becomes useful when a DSP is used to split the signal into hundreds
of bands. You can then be very precise about how much noise you remove, subtracting a lot at
(say) 8kHz, while leaving 8.1kHz virtually untouched.
But if this sounds too good to be true, it is. The noise spectrum (the sonic 'fingerprint') can only
be measured if there is an otherwise silent passage within the music, and if the fingerprint is not
accurate you will hear unpleasant side-effects. But let's assume that you have obtained a
perfect fingerprint. You might then expect a good restoration, with few or no side-effects. Yet
experience shows that spectral subtraction produces dry and dull results with unacceptable
artefacts. This is, in part, because the fingerprint is a snapshot of the random noise, accurate
only at the instant at which it is taken. Because the noise is constantly changing, the subtractive
algorithm is deriving its result from inappropriate data.
