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Deconvolution is a process of inverting the effect of convolution given the output signal and one of the input signals. If both input signals are unknown, we deal with blind deconvolution.
In this video, we are discussing 4 methods of non-blind deconvolution:
1. Deconvolution Using Frequency-Domain Division.
2. Deconvolution Via (Pseudo-)Inverse of the Convolution Matrix.
3. Wiener Filtering (Wiener Deconvolution).
4. Deconvolution Using Complex Cepstrum Liftering.
In case of any doubt in understanding, please, refer to the article above 🙂
00:00 Introduction
00:44 Deconvolution definition
01:44 Deconvolution for loudspeaker measurement
03:01 Deconvolution Using Frequency-Domain Division
04:15 Deconvolution in Python (scipy.signal) and Matlab
05:00 Deconvolution Via (Pseudo-)Inverse of the Convolution Matrix
07:15 Wiener Filtering (Wiener Deconvolution)
10:18 Deconvolution Using Complex Cepstrum Liftering
12:21 Summary
#dsp #deconvolution
