DEMO_AUDIOCOMPRESSION Audio compression using N-term approx
This demos shows how to do audio compression using best N-term
approximation of an WMDCT transform.
The signal is transformed using an orthonormal WMDCT transform.
Then approximations with a fixed number N of coefficients are obtained
by:
Linear approximation: The N coefficients with lowest frequency
index are kept.
Non-linear approximation: The N largest coefficients (in
magnitude) are kept.
The corresponding approximated signal can be computed using IWMDCT.
Figure 1: Rate-distorition plot
The figure shows the output Signal to Noise Ratio (SNR) as a function
of the number of retained coefficients.
Note: The inverse WMDCT is not needed for computing computing
SNRs. Instead Parseval theorem states that the norm of a signal equals
the norm of the sequence of its WMDCT coefficients.
Url: http://ltfat.github.io/doc/demos/demo_audiocompression.html
Package: ltfat