Description Usage Arguments Details Value See Also Examples
View source: R/makeFunctions.R
Compute the noise scale levels for each channel using the Signal to Noise Ratios
1 | sigmaSNR(signal, SNR)
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signal |
Noisefree multichannel input signal |
SNR |
A numeric vector specifying the desired Signal to Noise Ratio for each channel. |
The output noise scale levels (theoretical standard deviation for the process noise process in each channel) is governed by the blurred Signal-to-Noise Ratio (SNR) measured in decibels (dB) where,
SNR = 10 log_{10} (\frac{||k*f||^2}{σ^2)}
and k*f is the blurred signal, ||\cdot|| is the norm operator and σ is the standard deviation of the noise. Roughly speaking, noise levels are considered high, medium and low for the cases 10 dB, 20 dB and 30 dB respectively.
A numeric vector with m elements giving the scales (standard deviation of the noise in each channel) to achieve the desired SNR.
1 2 3 4 5 6 7 8 9 | n <- 1024
m <- 3
signal <- makeLIDAR(n)
blur <- gammaBlur(n, c(0.5, 0.75, 1), rep(1, m))
X <- blurSignal(signal, blur)
SNR <- 10*1:3
sigma <- sigmaSNR(X, SNR)
E <- multiNoise(n, sigma)
sigmaEst <- multiSigma(E)
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