基于小波变换的图像融合算法matlab仿真,带GUI界面,支持灰度图融合和彩色图融合两种模式+代码操作视频

function varargout = Image_Fusion(varargin) % IMAGE_FUSION MATLAB code for Image_Fusion.fig % IMAGE_FUSION, by itself, creates a new IMAGE_FUSION or raises the existing % singleton*. % % H = IMAGE_FUSION returns the handle to a new IMAGE_FUSION or the handle to % the existing singleton*. % % IMAGE_FUSION('CALLBACK',hObject,eventData,handles,...) calls the local % function named CALLBACK in IMAGE_FUSION.M with the given input arguments. % % IMAGE_FUSION('Property','Value',...) creates a new IMAGE_FUSION or raises the % existing singleton*. Starting from the left, property value pairs are % applied to the GUI before Image_Fusion_OpeningFcn gets called. An % unrecognized property name or invalid value makes property application % stop. All inputs are passed to Image_Fusion_OpeningFcn via varargin. % % *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one % instance to run (singleton)". % % See also: GUIDE, GUIDATA, GUIHANDLES % Edit the above text to modify the response to help Image_Fusion % Last Modified by GUIDE v2.5 13-May-2020 11:15:44 % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @Image_Fusion_OpeningFcn, ... 'gui_OutputFcn', @Image_Fusion_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 Image_Fusion is made visible. function Image_Fusion_OpeningFcn(hObject, eventdata, handles, varargin) % This function has no output args, see OutputFcn. % hObject handle to figure % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % varargin command line arguments to Image_Fusion (see VARARGIN) % Choose default command line output for Image_Fusion handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes Image_Fusion wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout = Image_Fusion_OutputFcn(hObject, eventdata, handles) % varargout cell array for returning output args (see VARARGOUT); % hObject handle to figure % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Get default command line output from handles structure varargout{1} = handles.output; % --- Executes on button press in pushbutton1. function pushbutton1_Callback(hObject, eventdata, handles) % hObject handle to pushbutton1 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) [filename1,PathName1] = uigetfile({'*.tif';'*.bmp';'*.jpg';'*.png'}); X1 = [PathName1 filename1]; if PathName1 ~=0 OriginImage1 = imread(X1); handles.OrginImage1=OriginImage1; guidata(hObject,handles); axes(handles.axes1); imshow(OriginImage1); end % --- Executes on button press in pushbutton2. function pushbutton2_Callback(hObject, eventdata, handles) % hObject handle to pushbutton2 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) [filename2,PathName2] = uigetfile({'*.tif';'*.bmp';'*.jpg';'*.png'}); X2 = [PathName2 filename2]; if PathName2 ~=0 OriginImage2 = imread(X2); handles.OrginImage2=OriginImage2; guidata(hObject,handles); axes(handles.axes2); imshow(OriginImage2); end % --- Executes on button press in pushbutton3. function pushbutton3_Callback(hObject, eventdata, handles) % hObject handle to pushbutton3 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) %图像融合 OriginImage1=handles.OrginImage1; OriginImage2=handles.OrginImage2; Image1=double(OriginImage1)/256; Image2=double(OriginImage2)/256; [c1,s1]=wavedec2(Image1,2,'sym3'); %将X1进行2维分解，并使用sym4小波进行变换 [c2,s2]=wavedec2(Image2,2,'sym3'); c=0.5*(c1+c2); %计算系数平均值 s=0.5*(s1+s2); X=waverec2(c,s,'sym3'); %进行小波重构 handles.X=X; guidata(hObject,handles); axes(handles.axes3); imshow(X); %评价指标 X=double(X); %对融合图像预处理 [C,R]=size(X); %相对标准差 s=size(size(Image1)); if s(2)==3 %判断是灰度图像还是RGB彩色图像 f1=rgb2gray(Image1); f2=rgb2gray(Image2); else f1=Image1; f2=Image2; end G1=double(f1); G2=double(f2); [m1,n1]=size(G1); [m2,n2]=size(G2); u1=(sum(G1(:)))/(m1*n1); u2=(sum(G2(:)))/(m2*n2); c1=0; c2=0; for i=1:m1 for j=1:n1 w1=G1(i,j)-u1; w2=G2(i,j)-u2; c1=c1+w1^2; c2=c2+w2^2; end end f1=sqrt(c1/(m1*n1)); f2=sqrt(c2/(m2*n2)); f=(f1-f2)/f1; set(handles.edit1,'String',num2str(f)); %峰值信噪比 MAX=255; %图像灰度级最大值 D=Image1-X; MES=sum(D(:).*D(:))./prod(size(Image1)); PSNR=10*log10(MAX^2/sqrt(MES)); set(handles.edit2,'String',num2str(PSNR)); %空间频率 RF=0; CF=0; for fi=1:C-1 for fj=1:R-1 RF=RF+(X(fi,fj)-X(fi,fj+1)).^2; end end RF=sqrt(RF/(C*R)); for fi=1:C-1 for fj=1:R-1 CF=CF+(X(fi,fj)-X(fi+1,fj)).^2; end end CF=sqrt(CF/(C*R)); SF=sqrt(RF+CF); set(handles.edit3,'String',num2str(SF)); %图像清晰度 n=C*R; m=1; for i=1:(C-1) for j=1:(R-1) x=X(i,j)-X(i,j+1); y=X(i,j)-X(i+1,j); z(m,1)=sqrt((x.^2+y.^2)/2); m=m+1; end end G=sum(z)/n; set(handles.edit4,'String',num2str(G)); %互信息 s1=size(size(X)); if s1(2)==3 %判断是灰度图像还是RGB彩色图像 a=rgb2gray(OriginImage1); a=double(a); b=rgb2gray(OriginImage2); b=double(b); else a=double(OriginImage1); b=double(OriginImage2); end [Ma,Na] = size(a); [Mb,Nb] = size(b); M=min(Ma,Mb); N=min(Na,Nb); %初始化直方图数组 hab = zeros(256,256); ha = zeros(1,256); hb = zeros(1,256); %归一化 if max(max(a))~=min(min(a)) a = (a-min(min(a)))./(max(max(a))-min(min(a))); else a = zeros(M,N); end if max(max(b))-min(min(b)) b = (b-min(min(b)))./(max(max(b))-min(min(b))); else b = zeros(M,N); end a = double(int16(a*255))+1; b = double(int16(b*255))+1; %统计直方图 for i=1:M for j=1:N indexx = a(i,j); indexy = b(i,j) ; hab(indexx,indexy) = hab(indexx,indexy)+1; %联合直方图 ha(indexx) = ha(indexx)+1; %a图直方图 hb(indexy) = hb(indexy)+1; %b图直方图 end end %计算联合信息熵 hsum = sum(sum(hab)); index = find(hab~=0); p = hab/hsum; Hab = sum(sum(-p(index).*log(p(index)))); %计算a图信息熵 hsum = sum(sum(ha)); index = find(ha~=0); p = ha/hsum; Ha = sum(sum(-p(index).*log(p(index)))); %计算b图信息熵 hsum = sum(sum(hb)); index = find(hb~=0); p = hb/hsum; Hb = sum(sum(-p(index).*log(p(index)))); %计算a图和b图的互信息 MI = Ha+Hb-Hab; set(handles.edit5,'String',num2str(MI)); %交叉熵 s=size(size(X)); if s(2)==3 %判断是灰度图像还是RGB彩色图像 f1=rgb2gray(OriginImage1); f2=rgb2gray(OriginImage2); else f1=OriginImage1; f2=OriginImage2; end G1=double(f1); G2=double(f2); [m1,n1]=size(G1); [m2,n2]=size(G2); m2=m1; n2=n1; X1=zeros(1,256); X2=zeros(1,256); result=0; %统计两图各灰度级像素 for i=1:m1 for j=1:n1 X1(G1(i,j)+1)=X1(G1(i,j)+1)+1; X2(G2(i,j)+1)=X2(G2(i,j)+1)+1; end end %计算两图各灰度级像素出现的概率 for k=1:256 P1(k)=X1(k)/(m1*n1); P2(k)=X2(k)/(m1*n1); if((P1(k)~=0)&&(P2(k)~=0)) result=P1(k)*log2(P1(k)/P2(k))+result; end end f=result; set(handles.edit6,'String',num2str(f)); function edit1_Callback(h