1 简介
图像质量评价含Matlab源码
2 部分代码
function varargout = IQA(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @IQA_OpeningFcn, ...
'gui_OutputFcn', @IQA_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end
if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT
% --- Executes just before IQA is made visible.
function IQA_OpeningFcn(hObject, eventdata, handles, varargin)
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
ResetButton_Callback(hObject, eventdata, handles)
% --- Outputs from this function are returned to the command line.
function varargout = IQA_OutputFcn(hObject, eventdata, handles)
% Get default command line output from handles structure
varargout{1} = handles.output;
% --- Executes on button press in BrowseImage.
function BrowseImage_Callback(hObject, eventdata, handles)
ResetButton_Callback(hObject, eventdata, handles);
global image;
[filename pathname] = uigetfile({'*.jpg';'*.bmp';'*.tif';'*.png'},'File Selector');
x = strcat(pathname, filename);
image=imread(x);
axes(handles.axes1);
imshow(image);
% --- Executes on button press in AddNoise.
function AddNoise_Callback(hObject, eventdata, handles)
global image;
global addnoisyimage;
global mean;
global variance;
global AdditiveNoiseMenu;
if (strcmp(AdditiveNoiseMenu, 'Gaussian'))
addnoisyimage = imnoise(image, 'Gaussian', mean, variance);
elseif (strcmp(AdditiveNoiseMenu, 'Poisson'))
addnoisyimage = imnoise(image, 'Poisson');
elseif (strcmp(AdditiveNoiseMenu, 'Select Additive Noise Type'))
addnoisyimage = image;
end
axes(handles.axes2);
imshow(addnoisyimage);
% --- Executes on button press in MultiNoise.
function MultiNoise_Callback(hObject, eventdata, handles)
global noisedensity;
global variance_multi;
global image;
global multinoisyimage;
global MultiplicativeNoiseMenu;
if (strcmp(MultiplicativeNoiseMenu, 'Salt & Pepper'))
multinoisyimage = imnoise(image, 'salt & pepper', noisedensity);
elseif (strcmp(MultiplicativeNoiseMenu, 'Speckle'))
multinoisyimage = imnoise(image, 'speckle', variance_multi);
elseif (strcmp(MultiplicativeNoiseMenu, 'Select Multiplicative Noise'))
multinoisyimage = image;
end
axes(handles.axes3);
imshow(multinoisyimage);
% --- Executes on button press in CheckPSNR.
function CheckPSNR_Callback(hObject, eventdata, handles)
global addnoisyimage;
global multinoisyimage;
global image;
global s;
global u;
global justforcontrol;
if (get(hObject, 'Value') == get(hObject,'Max'))
justforcontrol=1;
s=psnr(addnoisyimage, image);
u=psnr(multinoisyimage, image);
else
justforcontrol=0;
s='--';
u='--';
end
% Hint: get(hObject,'Value') returns toggle state of CheckPSNR
function s = psnr(addnoisyimage, image)
if(ndims(addnoisyimage)==3)
addnoisyimage = rgb2gray(addnoisyimage);
end
if(ndims(image)==3)
image = rgb2gray(image);
end
addnoisyimage=double(addnoisyimage);
image=double(image);
[m,n] = size(addnoisyimage);
peak=255*255*m*n;
noise = addnoisyimage - image;
nostotal = sum(sum(noise.*noise));
if nostotal == 0
s = 'INF'; %% INF. clean image
else
s = 10 * log10(peak./nostotal);
end
% --- Executes on button press in CheckSSIM.
function CheckSSIM_Callback(hObject, eventdata, handles)
global addnoisyimage;
global multinoisyimage;
global image;
global t;
global v;
global justforcontrol2;
K = [0.05 0.05];
window = ones(8);
L = 100;
Z = [0.01 0.03];
if (get(hObject, 'Value') == get(hObject,'Max'))
justforcontrol2=1;
t=ssim(addnoisyimage, image, Z, window, L);
v=ssim(multinoisyimage, image, Z, window, L);
else
justforcontrol2=0;
t='--';
v='--';
end
% Hint: get(hObject,'Value') returns toggle state of CheckSSIM
function [mssim] = ssim(img1, img2, Z, window, L)
if(ndims(img1)==3)
img1=rgb2gray(img1);
end
if(ndims(img2)==3)
img2=rgb2gray(img2);
end
[rows,cols]=size(img2);
img1=imresize(img1,[rows cols]);
if (nargin < 2 || nargin > 5)
mssim = -Inf;
ssim_map = -Inf;
return;
end
if (size(img1) ~= size(img2))
mssim = -Inf;
ssim_map = -Inf;
return;
end
[M N] = size(img1);
if (nargin == 2)
if ((M < 11) || (N < 11))
mssim = -Inf;
ssim_map = -Inf;
return
end
window = fspecial('gaussian', 11, 1.5); %
Z(1) = 0.01; % default settings
Z(2) = 0.03;
L = 255;
end
if (nargin == 3)
if ((M < 11) || (N < 11))
mssim = -Inf;
ssim_map = -Inf;
return
end
window = fspecial('gaussian', 11, 1.5);
L = 255;
if (length(Z) == 2)
if (Z(1) < 0 || Z(2) < 0)
mssim = -Inf;
ssim_map = -Inf;
return;
end
else
mssim = -Inf;
ssim_map = -Inf;
return;
end
end
if (nargin == 4)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mssim = -Inf;
ssim_map = -Inf;
return
end
L = 255;
if (length(Z) == 2)
if (Z(1) < 0 || Z(2) < 0)
mssim = -Inf;
ssim_map = -Inf;
return;
end
else
mssim = -Inf;
ssim_map = -Inf;
return;
end
end
if (nargin == 5)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mssim = -Inf;
ssim_map = -Inf;
return
end
if (length(Z) == 2)
if (Z(1) < 0 || Z(2) < 0)
mssim = -Inf;
ssim_map = -Inf;
return;
end
else
mssim = -Inf;
ssim_map = -Inf;
return;
end
end
img1 = double(img1);
img2 = double(img2);
% automatic downsampling
f = max(1,round(min(M,N)/256));
%downsampling by f
%use a simple low-pass filter
if(f>1)
lpf = ones(f,f);
lpf = lpf/sum(lpf(:));
img1 = imfilter(img1,lpf,'symmetric','same');
img2 = imfilter(img2,lpf,'symmetric','same');
img1 = img1(1:f:end,1:f:end);
img2 = img2(1:f:end,1:f:end);
end
C1 = (Z(1)*L)^2;
C2 = (Z(2)*L)^2;
window = window/sum(sum(window));
mu1 = filter2(window, img1, 'valid');
mu2 = filter2(window, img2, 'valid');
mu1_sq = mu1.*mu1;
mu2_sq = mu2.*mu2;
mu1_mu2 = mu1.*mu2;
sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq;
sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq;
sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2;
if (C1 > 0 && C2 > 0)
ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2));
else
numerator1 = 2*mu1_mu2 + C1;
numerator2 = 2*sigma12 + C2;
denominator1 = mu1_sq + mu2_sq + C1;
denominator2 = sigma1_sq + sigma2_sq + C2;
ssim_map = ones(size(mu1));
index = (denominator1.*denominator2 > 0);
ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index));
index = (denominator1 ~= 0) & (denominator2 == 0);
ssim_map(index) = numerator1(index)./denominator1(index);
end
mssim = mean2(ssim_map);
function edit1_Callback(hObject, eventdata, handles)
% Hints: get(hObject,'String') returns contents of edit1 as text
% str2double(get(hObject,'String')) returns contents of edit1 as a double
% --- Executes during object creation, after setting all properties.
function edit1_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on button press in AddNoiseResults.
function AddNoiseResults_Callback(hObject, eventdata, handles)
global u;
global v;
global s;
global t;
global justforcontrol;
global justforcontrol2;
if justforcontrol==1;
CheckPSNR_Callback(hObject, eventdata, handles)
end
if justforcontrol2==1;
CheckSSIM_Callback(hObject, eventdata, handles)
end
set(handles.PSNR_Add, 'string', s);
set(handles.SSIM_Add, 'string', t);
set(handles.PSNR_Multi, 'string', u);
set(handles.SSIM_Multi, 'string', v);
% --- Executes on button press in ResetButton.
function ResetButton_Callback(hObject, eventdata, handles)
global s;
global t
global u;
global v;
global q;
global justforcontrol;
global justforcontrol2;
global addnoisyimage;
global multinoisyimage;
global image;
global mean;
global variance;
global noisedensity;
global variance_multi;
global AdditiveNoiseMenu;
global MultiplicativeNoiseMenu;
t='--';
s='--';
u='--';
v='--';
q=0;
justforcontrol=0;
justforcontrol2=0;
image = ones(600,400);
addnoisyimage = image;
multinoisyimage = image;
axes(handles.axes1);
imshow(image);
axes(handles.axes2);
imshow(addnoisyimage);
axes(handles.axes3);
imshow(multinoisyimage);
set(handles.CheckPSNR, 'Value', q);
set(handles.CheckSSIM, 'Value', q);
set(handles.PSNR_Add, 'string', s);
set(handles.SSIM_Add, 'string', t);
set(handles.PSNR_Multi, 'string', u);
set(handles.SSIM_Multi, 'string', v);
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
if (strcmp(AdditiveNoiseMenu, 'Poisson'))
mean = 'N/A';
variance = 'N/A';
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
elseif (strcmp(AdditiveNoiseMenu, 'Gaussian'))
mean=0;
variance=0.01;
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
elseif (strcmp(AdditiveNoiseMenu, 'Select Additive Noise Type'))
mean=0;
variance=0;
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
end
if (strcmp(MultiplicativeNoiseMenu, 'Speckle'))
noisedensity = 'N/A';
variance_multi = 0.04;
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
elseif (strcmp(MultiplicativeNoiseMenu, 'Salt & Pepper'))
noisedensity = 0.05;
variance_multi = 'N/A';
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
elseif (strcmp(MultiplicativeNoiseMenu, 'Select Multiplicative Noise'))
noisedensity = 0;
variance_multi = 0;
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
end
% --- If Enable == 'on', executes on mouse press in 5 pixel border.
% --- Otherwise, executes on mouse press in 5 pixel border or over PSNR_Add.
function PSNR_Add_ButtonDownFcn(hObject, eventdata, handles)
function MeanValue_Callback(hObject, eventdata, handles)
% Hints: get(hObject,'String') returns contents of MeanValue as text
% str2double(get(hObject,'String')) returns contents of MeanValue as a double
global mean;
mean = str2double(get(handles.MeanValue,'string'));
% --- Executes during object creation, after setting all properties.
function MeanValue_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function VarianceValue_Callback(hObject, eventdata, handles)
% Hints: get(hObject,'String') returns contents of VarianceValue as text
% str2double(get(hObject,'String')) returns contents of VarianceValue as a double
global variance;
variance = str2double(get(handles.VarianceValue,'string'));
% --- Executes during object creation, after setting all properties.
function VarianceValue_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function NoiseDensityValue_Callback(hObject, eventdata, handles)
% Hints: get(hObject,'String') returns contents of NoiseDensityValue as text
% str2double(get(hObject,'String')) returns contents of NoiseDensityValue as a double
global noisedensity;
noisedensity = str2double(get(handles.NoiseDensityValue,'string'));
% --- Executes during object creation, after setting all properties.
function NoiseDensityValue_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on selection change in AdditiveNoiseMenu.
function AdditiveNoiseMenu_Callback(hObject, eventdata, handles)
% Hints: contents = cellstr(get(hObject,'String')) returns AdditiveNoiseMenu contents as cell array
% contents{get(hObject,'Value')} returns selected item from AdditiveNoiseMenu
global AdditiveNoiseMenu;
global mean;
global variance;
contents = cellstr(get(hObject,'String'));
AdditiveNoiseMenu = contents{get(hObject,'Value')};
if (strcmp(AdditiveNoiseMenu, 'Poisson'))
mean = 'N/A';
variance = 'N/A';
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
elseif (strcmp(AdditiveNoiseMenu, 'Gaussian'))
mean=0;
variance=0.01;
set(handles.MeanValue, 'string', mean);
set(handles.VarianceValue, 'string', variance);
end
% --- Executes during object creation, after setting all properties.
function AdditiveNoiseMenu_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on selection change in MultiplicativeNoiseMenu.
function MultiplicativeNoiseMenu_Callback(hObject, eventdata, handles)
% Hints: contents = cellstr(get(hObject,'String')) returns MultiplicativeNoiseMenu contents as cell array
% contents{get(hObject,'Value')} returns selected item from MultiplicativeNoiseMenu
global MultiplicativeNoiseMenu;
global noisedensity;
global variance_multi;
contents = cellstr(get(hObject,'String'));
MultiplicativeNoiseMenu = contents{get(hObject,'Value')};
if (strcmp(MultiplicativeNoiseMenu, 'Speckle'))
noisedensity = 'N/A';
variance_multi = 0.04;
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
elseif (strcmp(MultiplicativeNoiseMenu, 'Salt & Pepper'))
noisedensity = 0.05;
variance_multi = 'N/A';
set(handles.NoiseDensityValue, 'string', noisedensity);
set(handles.VarianceValue_Multi, 'string', variance_multi);
end
% --- Executes during object creation, after setting all properties.
function MultiplicativeNoiseMenu_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function VarianceValue_Multi_Callback(hObject, eventdata, handles)
% Hints: get(hObject,'String') returns contents of VarianceValue_Multi as text
% str2double(get(hObject,'String')) returns contents of VarianceValue_Multi as a double
global variance_multi;
variance_multi = str2double(get(handles.VarianceValue_Multi,'string'));
% --- Executes during object creation, after setting all properties.
function VarianceValue_Multi_CreateFcn(hObject, eventdata, handles)
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --------------------------------------------------------------------
function Untitled_1_Callback(hObject, eventdata, handles)
% hObject handle to Untitled_1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% --------------------------------------------------------------------
function Untitled_2_Callback(hObject, eventdata, handles)
% hObject handle to Untitled_2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)3 仿真结果
4 参考文献
[1]Wang, Z., & Bovik, A. C. (2009). Mean squared error: Love it or leave it? A new look at signal fidelity measures. IEEE signal processing magazine, 26(1), 98-117.
[2]Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 13(4), 600-612.
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