psnr.m

matlab仿真通过的降噪程序

clear all;
[y1,fs,bits]=wavread('f:\voise\3.wav');
%y1=y1/max(abs(y1));%归一化
wavwrite(y1,8000,8,'f:\wav\3.wav');
figure(1);
plot(y1);

[noise,fs1,bits1]=wavread('f:\voise\3_noise.wav');
y=mixsig(y1,noise,5);
%y=y/max(abs(y));%归一化
wavwrite(y,8000,8,'f:\wav\mymasking_s&w.wav');%0db带噪信号
figure(2);
plot(y);
%clear all;
%[y1,fs,bits]=wavread('8k8bit.wav'); % Actual Signal
%[noise,fs1,bits1]=wavread('8k8bit_noise.wav');
%y=mixsig(y1,noise, 10);
%wavwrite(y,8000,8,'f:\a\mymasking_s&w.wav');
%figure(1);
%plot(y);
frame = 256;    % Defining frame size
%for k = 1:2560, % Loop for first 50 frames(0.5 seconds) of noise
%  y_temp(k) = y(k);
%end;
shift=64;
win=hamming(256);
signal(1)=y(1);
for j1 = 2:length(y),
 signal(j1) = y(j1)-0.9375*y(j1-1);  %preemphasize
end;

ps_noise=zeros(length(signal)/frame,frame);
frame_temp = zeros(length(signal)/frame,frame);
%length1 = length(y_temp);   % length of the noise samples(first 4000 samples)
%ps_noise = zeros(length1/frame,frame);
%frame_temp = zeros(length1/frame,frame);
%hh = 0; 
 %  for k = 1 : length1/frame,
 %       for l = 1 : frame,
%          b(l) = y_temp(hh+l);
%        end;
%        hh = hh + frame;
%        frame_temp(k,1:frame) = fft(b);                      %fft for the first 50 frames
%        ps_noise(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))/frame;
%        A(1,k) = (sum(ps_noise(k,1:frame)));          % Sum of the power spectral densities of samples within a frame

%  end;
%threshold = sum(A)*frame/length1;            % setting the threshold for the noise(frame noise)

hh = 0; 
   for k = 1 : 5,
       for l = 1 : frame,
          b(l) = signal(hh+l);
      end;
        hh = hh + frame;
        frame_temp(k,1:frame) = fft(b);                      %fft for the first 50 frames
        ps_noise(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))/frame;
        %ps_noise(1,1:frame)= (sum(ps_noise(1:k,l))/20);          % Sum of the power spectral densities of samples within a frame

    end;
    %ps_noise=zeros(length(signal)/frame,frame);
    %ps_noise(1,1:frame)= sum(A)/20;            % setting the threshold for the noise(frame noise)
    ps_noise(1,1:frame)= (sum(ps_noise(1:k,1:frame))/5);
    frame_temp_initial(1:frame)=sum(frame_temp(k,1:frame))/k;



head = 0; 
mm=1;
nn=1;
%sum1=0;
%sum2=0;
% START OF THE NOISE ELIMINATION THROUGH SPECTRAL SUBTRACTION BASED ON THE THRESHOLD SET

  % for k = 1 : length(signal)/shift-3,
  for k = 1 : length(signal)/frame,
        for m = 1 : frame,
          abc1(m) = signal(head+m);
          %
        end;
        %abc1=abc1.*win';
       % head = head +shift;
        head=head+frame;
        
        frame_temp(k,1:frame) = fft(abc1);% FFT OF THE SIGNAL + NOISE FRAME BY FRAME

        frame_angle(k,1:frame) = angle(fft(abc1));% ANGLE OF FFT OF THE SIGNAL + NOISE FRAME BY FRAME

        ps_signal(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))./frame;
        
        ps_temp=zeros(1,frame);
        ps_temp(1,1:frame)=ps_signal(k,1:frame);
        
        
        if k==1
            ps_noise(k,1:frame)=0.98*ps_noise(1,1:frame)+0.02*ps_signal(k,1:frame);
           % ps_signal(k,1:frame)=0.98*ps_signal(k,1:frame)+0.02*ps_signal(k,1:frame);
        else
           ps_noise(k,1:frame)=0.99*ps_noise(k-1,1:frame)+0.01*ps_signal(k,1:frame);
           ps_signal(k,1:frame)=0.1*ps_signal(k-1,1:frame)+0.9*ps_signal(k,1:frame);
        end
        
        frame_ps(1,k) = (sum(ps_signal(k,1:frame)));
        frame_pn(1,k)=sum(ps_noise(k,1:frame));
        
        if k==1
            sum1(k)=frame_ps(1,k)-frame_pn(1,k);
            sum2(k)=frame_pn(1,k);
        else
            sum1(k)=sum1(k-1)+frame_ps(1,k)-frame_pn(1,k);
            sum2(k)=sum2(k-1)+frame_pn(1,k);
        end
        psnr(1,k)=10*log10(sum1(k)/sum2(k));
        asnr(1,k)=10*log10(abs((frame_ps(1,k)-frame_pn(1,k))/frame_pn(1,k)));
          
        %psnr(1,k)=10*log10(sum(abs(frame_ps(1,1:k)-frame_pn(1,1:k)))/sum(frame_pn(1,1:k)));
        
        %ps_final(1,k) = frame_ps(1,k) - threshold;
        %aa=0.8;
        ps_final(1,k) = frame_ps(1,k)- 0.5*frame_pn(1,k);    
        
      
      
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

end

  for k=1:30
      ppp_signal(k,1:frame)=ps_signal(k,1:frame);
      ppp_noise(k,1:frame)=ps_noise(k,1:frame);
  end