MATLAB.zip_灰度图值

function varargout = txfg(varargin) % TXFG M-file for txfg.fig % TXFG, by itself, creates a new TXFG or raises the existing % singleton*. % H = TXFG returns the handle to a new TXFG or the handle to % the existing singleton*. % TXFG('CALLBACK',hObject,eventData,handles,...) calls the local % function named CALLBACK in TXFG.M with the given input arguments. % TXFG('Property','Value',...) creates a new TXFG or raises the % existing singleton*. Starting from the left, property value pairs are % applied to the GUI before txfg_OpeningFcn gets called. An % unrecognized property name or invalid value makes property application % stop. All inputs are passed to txfg_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 txfg % Last Modified by GUIDE v2.5 17-May-2013 22:41:16 % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @txfg_OpeningFcn, ... 'gui_OutputFcn', @txfg_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 txfg is made visible. function txfg_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 txfg (see VARARGIN) % Choose default command line output for txfg handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes txfg wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout = txfg_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; % -------------------------------------------------------------------- function wenjian_Callback(hObject, eventdata, handles) % hObject handle to wenjian (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % -------------------------------------------------------------------- function suanfaxz_Callback(hObject, eventdata, handles) % hObject handle to suanfaxz (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % -------------------------------------------------------------------- function fangchafa_Callback(hObject, eventdata, handles) % hObject handle to fangchafa (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global rgbimage; x=rgbimage; %figure; %imshow(x); [m,n]=size(x); N=m*n; num=zeros(1,256); p=zeros(1,256); for i=1:m for j=1:n num(x(i,j)+1)=num(x(i,j)+1)+1; end end for i=0:255; p(i+1)=num(i+1)/N; end totalmean=0; for i=0:255; totalmean=totalmean+i*p(i+1); end maxvar=0; for k=0:255 kk=k+1; zerosth=sum(p(1:kk)); firsth=0; for h=0:k firsth=firsth+h*p(h+1); end var=totalmean*zerosth-firsth; var=var*var; var=var/(zerosth*(1-zerosth)+0.01); var=sqrt(var); if(var>maxvar) maxvar=var; point=k; end end threshold=point; for i=1:m for j=1:n if x(i,j)>point bin(i,j)=1; else bin(i,j)=0; end end end axes(handles.axes7); imshow(bin); % -------------------------------------------------------------------- function zishiying_Callback(hObject, eventdata, handles) % hObject handle to zishiying (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global rgbimage; SE = strel('diamond',4); BW1 = rgbimage; BW2 = imerode(BW1,SE); BW3 = imdilate(BW2,SE); BW4 = BW1-BW3; %rgb转灰度 if isrgb(BW4)==1 I_gray=rgb2gray(BW4); else I_gray=BW4; end figure('NumberTitle', 'off', 'Name', '自适应处理结果') subplot(2,2,1); imshow(I_gray); title('灰度图像'); I_double=double(I_gray);%转化为双精度 [wid,len]=size(I_gray); colorlevel=256; %灰度级 hist=zeros(colorlevel,1);%直方图 %threshold=128; %初始阈值 %计算直方图 for i=1:wid for j=1:len m=I_gray(i,j)+1; hist(m)=hist(m)+1; end end hist=hist/(wid*len);%直方图归一化 miuT=0; for m=1:colorlevel miuT=miuT+(m-1)*hist(m); end xigmaB2=0; for mindex=1:colorlevel threshold=mindex-1; omega1=0; omega2=0; for m=1:threshold-1 omega1=omega1+hist(m); end omega2=1-omega1; miu1=0; miu2=0; for m=1:colorlevel if m<threshold miu1=miu1+(m-1)*hist(m); else miu2=miu2+(m-1)*hist(m); end end miu1=miu1/omega1; miu2=miu2/omega2; xigmaB21=omega1*(miu1-miuT)^2+omega2*(miu2-miuT)^2; xigma(mindex)=xigmaB21; if xigmaB21>xigmaB2 finalT=threshold; xigmaB2=xigmaB21; end end fT=finalT/255%阈值归一化 T=graythresh(I_gray)%matlab函数求阈值 for i=1:wid for J=1:len if I_double(i,j)>finalT bn(i,j)=1; else bin(i,j)=0; end end end subplot(2,2,2); imshow(bin); title('bin'); subplot(2,2,3.2); plot(1:colorlevel,xigma); % -------------------------------------------------------------------- function yibanyuzhi_Callback(hObject, eventdata, handles) % hObject handle to yibanyuzhi (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global rgbimage; f=rgb2gray(rgbimage); f=im2double(f); T=0.5*(min(f(:))+max(f(:)));% 计算初始阈值 done=false; while ~done g=f>=T;%阈值比较 Tn=0.5*(mean(f(g))+mean(f(~g)));% Tnext=0.5*(mean(d(g))+mean(d(~g)))计算当前阈值下，分割后图像均值，并作为下一次的阈值 done=abs(T-Tn)<0.1;%判断是否可以终止分割 T=Tn; end display('迭代阈值(T)'); T r=im2bw(f,T); figure('NumberTitle', 'off', 'Name', '一般阈值法处理结果') subplot(2,2,1); imshow(f); title('原始图像'); subplot(2,2,2),imshow(r); title('全图阈值迭代法'); Th=graythresh(f); display('阈值(T)-Otsu法'); Th s=im2bw(f,Th); subplot(2,2,3),title('全图阈值-Otsu法'); se=strel('disk',10); ft=imtophat(f,se); Thr=graythresh(ft); display('局部阈值') Thr lt=im2bw(ft,Thr); subplot(2,2,4),imshow(lt); title('局部阈值'); % -------------------------------------------------------------------- function zuidashangfa_Callback(hObject, eventdata, handles) % hObject handle to zuidashangfa (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global rgbimage; a=rgbimage; count=imhist(a); [m,n]=size(a); N=m*n; L=256; count=count/N;%%每一个像素的分布概率 count for i=1:L if count(i)~=0 st=i-1; break; end end st for i=L:-1:1 if count(i)~=0 nd=i-1; break; end end nd f=count(st+1:nd+1); %f是每个灰度出现的概率 size(f) E=[]; for Th=st:nd-1 %%%设定初始分割阈值为Th av1=0; av2=0; Pth=sum(count(1:Th+1)); %第一类的平均相对熵为 for i=0:Th av1=av1-count(i+1)/Pth*log(count(i+1)/Pth+0.00001); end %第二类的平均相对熵为 for i=Th+1:L-1 av2=av2-count(i+1)/(1-Pth)*log(count(i+1)/(1-Pth)+0.00001); end E(Th-st+1)=av1+av2; end position=find(E==(max(E))); th=st+position-1 for i=1:m for j=1:n if a(i,j)>th