TP3_8: Noise removal done.

This commit is contained in:
Diogo Cordeiro 2020-12-31 23:11:10 +00:00
parent 99987da72c
commit 4b900c759d
18 changed files with 162 additions and 34 deletions

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@ -10,6 +10,7 @@ s = y(:,1);
% F: vector of cyclical frequencies
% T: vector of time instants
% P: power spectral density (PSD)
% signal, window, noverlap, nfft, fs
[S, F, T, P] = spectrogram(s, 128, 96, 128, Fs);
figure(1)

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@ -1,34 +0,0 @@
%% clean environment
clear; close all; clc
%% read input
[signal, fs] = audioread("Canto1.mp3");
%% Compute the FFT
signal_length = length(signal);
fhat = fft(signal, signal_length);
PSD = fhat.*conj(fhat)/signal_length; % Power spectrum density
%[S, freq, T, PSDlel] = spectrogram(signal, 128, 96, 128, Fs);
% signal, window, noverlap, nfft, fs
freq_vector = linspace(1, fs, signal_length);
L = 1:floor(signal_length/2);
cutoff_indices = abs(PSD)>0.002;
PSD_clean = PSD.*cutoff_indices;
fhat_filtered = cutoff_indices.*fhat;
signal_filtered = ifft(fhat_filtered);
figure(1)
plot(PSD)
figure(2)
plot(PSD_clean)
figure(3)
plot(signal)
figure(4)
plot(signal_filtered)
%% output
audiowrite('restored.flac', signal_filtered, fs);

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@ -0,0 +1,58 @@
%% Inicialização do ambiente
clear; close all; clc
%% >Exercício 8<
%% Input
[y, Fs] = audioread("Canto1.mp3"); % Signal and Sampling Frequency
signal = y(:,1); % Discard second channel
Fn = Fs/2; % Nyquist Frequency (Hz)
L = length(signal); % Signal Length
%% Find the noise
dft_signal = fft(signal)./L; % Fourier Transform
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
%% Filter
%signal_filtered = filter(DiogoEliseu_TP3_8_butterworth_2nd_order_filter,signal);
signal_filtered = filter(DiogoEliseu_TP3_8_butterworth_filter,signal);
%% Filtered signal
dft_signal_filtered = fft(signal_filtered)/L; % Fourier Transform
%% Output
signal_power = abs(dft_signal(1:(L/2+1)));
figure(1)
subplot(2,3,1)
hold on
plot(Fv, signal_power)
grid
marks = [2850, 3020, 7000, 7150];
plot(2850, signal_power(2850), 'r*')
plot(3020, signal_power(3020), 'r*')
plot(7000, signal_power(7000), 'r*')
plot(7150, signal_power(7150), 'r*')
xlabel("Frequência (Hz)"); ylabel("|H_{1}(f)|"); title("DFT do Sinal")
hold off
subplot(2,3,4)
plot(Fv, abs(dft_signal_filtered(1:(L/2+1))))
grid
xlabel("Frequência (Hz)"); ylabel("|H_{1}(f)|"); title("DFT do Sinal Filtrado")
subplot(2,3,2)
plot(Fv, signal(1:(L/2+1)))
grid
xlabel("Frequência (Hz)"); ylabel("Amplitude"); title("Sinal")
subplot(2,3,5)
plot(Fv, signal_filtered(1:(L/2+1)))
grid
xlabel("Frequência (Hz)"); ylabel("Amplitude"); title("Sinal Filtrado")
subplot(2,3,3)
plot(Fv, mag2db(signal_power))
grid
xlabel("Frequência (Hz)"); ylabel("Ganho (dB)"); title("Ganho do Sinal")
subplot(2,3,6)
plot(Fv, mag2db(abs(dft_signal_filtered(1:(L/2+1)))))
grid
xlabel("Frequência (Hz)"); ylabel("Ganho (dB)"); title("Ganho do Sinal Filtrado")
%sound(signal_filtered, Fs);
%audiowrite('canto1_butterworth.flac', signal_filtered, Fs);

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@ -0,0 +1,21 @@
function Hd = DiogoEliseu_TP3_8_final2
%DIOGOELISEU_TP3_8_FINAL2 Returns a discrete-time filter object.
% MATLAB Code
% Generated by MATLAB(R) 9.8 and Signal Processing Toolbox 8.4.
% Generated on: 31-Dec-2020 16:39:59
% Butterworth Bandpass filter designed using FDESIGN.BANDPASS.
% All frequency values are in Hz.
Fs = 44100; % Sampling Frequency
N = 2; % Order
Fc1 = 2850; % First Cutoff Frequency
Fc2 = 7150; % Second Cutoff Frequency
% Construct an FDESIGN object and call its BUTTER method.
h = fdesign.bandpass('N,F3dB1,F3dB2', N, Fc1, Fc2, Fs);
Hd = design(h, 'butter');
% [EOF]

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@ -0,0 +1,27 @@
function Hd = DiogoEliseu_TP3_8_final_filter
%DIOGOELISEU_TP3_8_FINAL_FILTER Returns a discrete-time filter object.
% MATLAB Code
% Generated by MATLAB(R) 9.8 and Signal Processing Toolbox 8.4.
% Generated on: 31-Dec-2020 19:24:38
% Butterworth Bandpass filter designed using FDESIGN.BANDPASS.
% All frequency values are in Hz.
Fs = 44100; % Sampling Frequency
Fstop1 = 2850; % First Stopband Frequency
Fpass1 = 3020; % First Passband Frequency
Fpass2 = 7000; % Second Passband Frequency
Fstop2 = 7150; % Second Stopband Frequency
Astop1 = 96; % First Stopband Attenuation (dB)
Apass = 1; % Passband Ripple (dB)
Astop2 = 104; % Second Stopband Attenuation (dB)
match = 'stopband'; % Band to match exactly
% Construct an FDESIGN object and call its BUTTER method.
h = fdesign.bandpass(Fstop1, Fpass1, Fpass2, Fstop2, Astop1, Apass, ...
Astop2, Fs);
Hd = design(h, 'butter', 'MatchExactly', match);
% [EOF]

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@ -0,0 +1,55 @@
%% Inicialização do ambiente
clear; close all; clc
%% >Exercício 8<
%% Input
[y, Fs] = audioread("Canto1.mp3"); % Signal and Sampling Frequency
signal = y(:,1); % Discard second channel
Fn = Fs/2; % Nyquist Frequency (Hz)
L = length(signal); % Signal Length
%% Compute the DFT
dft = fft(signal)./L;
magnitude = 10.*log10(abs(dft).^2); % power is squared, thus 10
Fv = linspace(0, 1, L)*Fn; % Frequency Vector
%% High-pass Filter
not_to_cutoff_indices = magnitude > -96;
dft_filtered = not_to_cutoff_indices.*dft;
magnitude_filtered = not_to_cutoff_indices.*magnitude;
signal_filtered = ifft(dft_filtered.*L);
%% Output
Fv_half = linspace(0, 1, fix(L/2)+1)*Fn;
y = abs(dft(1:(L/2+1)));
y_filtered = abs(dft_filtered(1:(L/2+1)));
figure(1)
subplot(2,3,1)
plot(Fv_half, y)
grid
xlabel("Frequência (Hz)"); ylabel("|H_{1}(f)|"); title("DFT do Sinal")
subplot(2,3,4)
plot(Fv_half, y_filtered)
grid
xlabel("Frequência (Hz)"); ylabel("|H_{1}(f)|"); title("DFT do Sinal Filtrado")
subplot(2,3,2)
plot(Fv_half, signal(1:(L/2+1)))
grid
xlabel("Frequência (Hz)"); ylabel("Amplitude"); title("Sinal")
subplot(2,3,5)
plot(Fv_half, y_filtered)
grid
xlabel("Frequência (Hz)"); ylabel("Amplitude"); title("Sinal Filtrado")
subplot(2,3,3)
%plot(Fv, magnitude);
plot(Fv_half, mag2db(y))
grid
xlabel("Frequência (Hz)"); ylabel("Ganho (dB)"); title("Ganho do Sinal")
subplot(2,3,6)
plot(Fv_half, mag2db(y_filtered))
grid
xlabel("Frequência (Hz)"); ylabel("Ganho (dB)"); title("Ganho do Sinal Filtrado")
%sound(signal_filtered, Fs);
%audiowrite('canto1_high_pass.flac', signal_filtered, Fs);

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