degrade

PURPOSE ^

DEGRADE an image using a PSF spatially invariant h (Gaussian low-pass filter

SYNOPSIS ^

function [Id,PSF,H,noise,Blurred]=degrade(Im,fc,Val_min,lim_frec,vari);

DESCRIPTION ^

   DEGRADE an image using a PSF spatially invariant h (Gaussian low-pass filter
   with normalized cutoff frequency fc, 0<fc<1 -1 is the Nyquist frequency-).
   Also, it includes isotropic colored noise in the 0<[f1,f2]<1 band of a
   given variance.

   NOTE THAT: In order to allow frequencies higher than fc, there is a parameter
   'val' in the frequency response.
   Since we are normlaizing the PSF in order to keep the DC component, the value
   of the frequency response for high frequencies is not 'val' but slightly higher.
   In any case, the function gives back H (frequency response of the blurring filter)
   With val=0 no the normalization is not modified.

   The degraded image is:
    Id = conv2(Im,h) + noise;


    INPUTS:

    Im: Dergraded image.
    fcorte: Cutoff PSF frequency
    val: value to control the response value above fc.
    [f1 f2]: Vector of frecuencies defining the band of the colored noise.
    vari: variance of the aditive noise.

    OUTPUTS:

    Id:  Degraded image
    PSF: Peak Spread Function
    H: Frequency response H=abs(freqz2(PSF));
    noise: added noise
    blurred: Blurred image (before adding the noise)

    USE:
    [Id,PSF,H,noise,Blurred] = degrade(Im,fcorte,val,[f1 f2],vari);

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 %
0002 %   DEGRADE an image using a PSF spatially invariant h (Gaussian low-pass filter
0003 %   with normalized cutoff frequency fc, 0<fc<1 -1 is the Nyquist frequency-).
0004 %   Also, it includes isotropic colored noise in the 0<[f1,f2]<1 band of a
0005 %   given variance.
0006 %
0007 %   NOTE THAT: In order to allow frequencies higher than fc, there is a parameter
0008 %   'val' in the frequency response.
0009 %   Since we are normlaizing the PSF in order to keep the DC component, the value
0010 %   of the frequency response for high frequencies is not 'val' but slightly higher.
0011 %   In any case, the function gives back H (frequency response of the blurring filter)
0012 %   With val=0 no the normalization is not modified.
0013 %
0014 %   The degraded image is:
0015 %    Id = conv2(Im,h) + noise;
0016 %
0017 %
0018 %    INPUTS:
0019 %
0020 %    Im: Dergraded image.
0021 %    fcorte: Cutoff PSF frequency
0022 %    val: value to control the response value above fc.
0023 %    [f1 f2]: Vector of frecuencies defining the band of the colored noise.
0024 %    vari: variance of the aditive noise.
0025 %
0026 %    OUTPUTS:
0027 %
0028 %    Id:  Degraded image
0029 %    PSF: Peak Spread Function
0030 %    H: Frequency response H=abs(freqz2(PSF));
0031 %    noise: added noise
0032 %    blurred: Blurred image (before adding the noise)
0033 %
0034 %    USE:
0035 %    [Id,PSF,H,noise,Blurred] = degrade(Im,fcorte,val,[f1 f2],vari);
0036 
0037 function [Id,PSF,H,noise,Blurred]=degrade(Im,fc,Val_min,lim_frec,vari);
0038 
0039 N=size(Im);
0040 
0041 Numpf = 11;
0042 
0043 [f1,f2] = freqspace(Numpf,'meshgrid');
0044 Hd = ones(Numpf);
0045 r = sqrt(f1.^2 + f2.^2);
0046 Hd(r>fc) = Val_min;
0047 win = fspecial('gaussian',Numpf,2);
0048 win = win ./ max(win(:));
0049 PSF = fwind2(Hd,win);
0050 PSF=PSF/sum(sum(PSF));
0051 H=abs(freqz2(PSF));
0052 
0053 Im2 = ampliaconborde(Im,10);
0054 
0055 Im2 = conv2(Im2,PSF,'same');
0056 
0057 Blurred = Im2(11:11+N(1)-1,11:11+N(2)-1);
0058 
0059 [f1,f2] = freqspace(N,'meshgrid');
0060 r = sqrt(f1.^2 + f2.^2);
0061 Hruido=(r>=lim_frec(1))&(r<=lim_frec(2));
0062 tfruido=Hruido.*exp(sqrt(-1)*2*pi*rand(N));
0063 ruido=real(ifft2(fftshift(tfruido)));
0064 varruido=var(ruido(:));
0065 
0066 noise = sqrt(vari)*ruido/sqrt(varruido);
0067 
0068 Id = Blurred + noise;

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