matlab数字图像GUI

【实例截图】

【核心代码】

function varargout = image_processing(varargin)
% IMAGE_PROCESSING MATLAB code for image_processing.fig
%      IMAGE_PROCESSING, by itself, creates a new IMAGE_PROCESSING or raises the existing
%      singleton*.
%
%      H = IMAGE_PROCESSING returns the handle to a new IMAGE_PROCESSING or the handle to
%      the existing singleton*.
%
%      IMAGE_PROCESSING('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in IMAGE_PROCESSING.M with the given input arguments.
%
%      IMAGE_PROCESSING('Property','Value',...) creates a new IMAGE_PROCESSING or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before image_processing_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to image_processing_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_processing

% Last Modified by GUIDE v2.5 22-Apr-2017 15:16:04

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @image_processing_OpeningFcn, ...
                   'gui_OutputFcn',  @image_processing_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_processing is made visible.
function image_processing_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_processing (see VARARGIN)

% Choose default command line output for image_processing
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes image_processing wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = image_processing_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
axis off;
varargout{1} = handles.output;


% --- Executes on button press in pushbutton1.
function pushbutton1_Callback(hObject, eventdata, handles)
    global M;
    ima_gray=image_gray(M);
    imshow(ima_gray);
% 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)


% --- Executes on button press in pushbutton2.
function pushbutton2_Callback(hObject, eventdata, handles)
    global M;
    ima_gray=image_gray(M);
    [i,j]=size(ima_gray);
    prompt = {'请输入阈值:'};
    dlg_title = '提示';
    num_lines = 1;
    def = {'5'};
    value_i = inputdlg(prompt,dlg_title,num_lines);
    threshold_value=str2double(value_i);
    for a=1:i
        for b=1:j
            if ima_gray(a,b)<threshold_value
                ima_gray(a,b)=0;
            else
                ima_gray(a,b)=1;
            end
        end
    end
    ima_gray=mat2gray(ima_gray);
    imshow(ima_gray);
    
        
% 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)


% --- Executes on button press in pushbutton3.
function pushbutton3_Callback(hObject, eventdata, handles)
    global M;
    ima_red=M(:,:,1);
    ima_green=M(:,:,2);
    ima_blue=M(:,:,3);
    img_red=mid_filter(ima_red,6);
    img_green=mid_filter(ima_green,6);
    img_blue=mid_filter(ima_blue,6);
    image(:,:,1)=img_red;
    image(:,:,2)=img_green;
    image(:,:,3)=img_blue;
    imshow(image);
    
    
% 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)


% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
    global M;
    if size(M,1)<2;
        msgbox('请先打开图片');
    end
    ima_red=M(:,:,1);
    ima_green=M(:,:,2);
    ima_blue=M(:,:,3);
    processing_red=low_pass_filter(ima_red);
    processing_green=low_pass_filter(ima_green);
    processing_blue=low_pass_filter(ima_blue);
    image(:,:,1)=processing_red;
    image(:,:,2)=processing_green;
    image(:,:,3)=processing_blue;
    imshow(image);
        
% hObject    handle to pushbutton4 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton5.
function pushbutton5_Callback(hObject, eventdata, handles)
    global M;
    prompt = {'请输入滤波核大小:'};
    dlg_title = '提示';
    num_lines = 1;
    def = {'5'};
    value_i = inputdlg(prompt,dlg_title,num_lines);
    N=str2double(value_i);
    d=avg_filter(M,N);    
    imshow(d);
    
    
% hObject    handle to pushbutton5 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton6.
function pushbutton6_Callback(hObject, eventdata, handles)
    global M;
    %滤波核大小
    ima_red=M(:,:,1);
    ima_green=M(:,:,2);
    ima_blue=M(:,:,3);
    prompt = {'请输入滤波器大小:'};
    dlg_title = '提示';
    num_lines = 1;
    value_i = inputdlg(prompt,dlg_title,num_lines);
    N=str2double(value_i);
    sigma=1.7;
    img_red=image_gaussian(ima_red,sigma,N);
    img_green=image_gaussian(ima_green,sigma,N);
    img_blue=image_gaussian(ima_blue,sigma,N);
    img(:,:,1)=img_red;
    img(:,:,2)=img_green;
    img(:,:,3)=img_blue;
    imshow(img);
    
% hObject    handle to pushbutton6 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton7.
function pushbutton7_Callback(hObject, eventdata, handles)
    global M;
    ima_red=M(:,:,1);
    ima_green=M(:,:,2);
    ima_blue=M(:,:,3);
    histogram_red=histogram(ima_red);
    histogram_green=histogram(ima_green);
    histogram_blue=histogram(ima_blue);
    figure,
    subplot(1,3,1);plot(histogram_red),title('红色通道');
    xlim([0 255])
    subplot(1,3,2),plot(histogram_green),title('绿色通道');
    xlim([0 255])
    subplot(1,3,3),plot(histogram_blue),title('蓝色通道');
    xlim([0 255])
%     ima=imread('1.jpg');
%     ima_gaussian=image_gaussian(ima,2,500);
% hObject    handle to pushbutton7 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton8.
function pushbutton8_Callback(hObject, eventdata, handles)%每个通道不一样，不能按照一个通道来
    global M;
    ima_gray=image_gray(M);
    [i,j]=size(ima_gray);
    threshold_value=150;
    for a=1:i
        for b=1:j
            if ima_gray(a,b)<threshold_value
                ima_gray(a,b)=0;
            else
                ima_gray(a,b)=1;
            end
        end
    end
    ima_gray=mat2gray(ima_gray);
    IMG=ima_gray;
    [row,col]=size(IMG);
    figure,imshow(IMG);title('二值化');
    for i=1:row-1
         for j=1:col-1
             if(IMG(i,j 1)&&IMG(i 1,j))     %若S中为1的位置全为1则为1
                IMG(i,j)=1;    %正向判断1
             else
                IMG(i,j)=0;  
             end
         end
     end
     figure,imshow(IMG);title('腐蚀');
    

    
%     figure,
%     subplot(1,3,1);plot(histogram_red),title('红色通道');
%     xlim([0 255])
%     subplot(1,3,2),plot(histogram_green),title('绿色通道');
%     xlim([0 255])
%     subplot(1,3,3),plot(histogram_blue),title('蓝色通道');
%     xlim([0 255])
    
    
% hObject    handle to pushbutton8 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton9.
function pushbutton9_Callback(hObject, eventdata, handles)
    global M;
    [m,n,q]=size(M);  
    img=double(M);
    %%canny边缘检测的前两步相对不复杂，所以我就直接调用系统函数了
    %%高斯滤波
    w=fspecial('gaussian',[5 5]);
    img=imfilter(img,w,'replicate');

%%sobel边缘检测
w=fspecial('sobel');
img_w=imfilter(img,w,'replicate');      %求横边缘
w=w';
img_h=imfilter(img,w,'replicate');      %求竖边缘
img=sqrt(img_w.^2 img_h.^2);        %注意这里不是简单的求平均，而是平方和在开方。我曾经好长一段时间都搞错了

%%下面是非极大抑制
new_edge=zeros(m,n);
for i=2:m-1
    for j=2:n-1
        Mx=img_w(i,j);
        My=img_h(i,j);
        
        if My~=0
            o=atan(Mx/My);      %边缘的法线弧度
        elseif My==0 && Mx>0
            o=pi/2;
        else
            o=-pi/2;            
        end
        
        %Mx处用My和img进行插值
        adds=get_coords(o);      %边缘像素法线一侧求得的两点坐标，插值需要       
        M1=My*img(i adds(2),j adds(1)) (Mx-My)*img(i adds(4),j adds(3));   %插值后得到的像素，用此像素和当前像素比较 
        adds=get_coords(o pi);%边缘法线另一侧求得的两点坐标，插值需要
        M2=My*img(i adds(2),j adds(1)) (Mx-My)*img(i adds(4),j adds(3));   %另一侧插值得到的像素，同样和当前像素比较
        
        isbigger=(Mx*img(i,j)>M1)*(Mx*img(i,j)>=M2) (Mx*img(i,j)<M1)*(Mx*img(i,j)<=M2); %如果当前点比两边点都大置1
        
        if isbigger
           new_edge(i,j)=img(i,j); 
        end        
    end
end


%%下面是滞后阈值处理
up=120;     %上阈值
low=100;    %下阈值
set(0,'RecursionLimit',10000);  %设置最大递归深度
for i=1:m
    for j=1:n
      if new_edge(i,j)>up &&new_edge(i,j)~=255  %判断上阈值
            new_edge(i,j)=255;
            new_edge=connect(new_edge,i,j,low);
      end
    end
end
imshow(new_edge==255);



% hObject    handle to pushbutton9 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton10.
function pushbutton10_Callback(hObject, eventdata, handles)
    global M;
    u=image_gray(M);
    F=double(M); 
    U=double(u); 
    [H,W]=size(u); 
    uSobel=u; 
    % ms=0; 
    % ns=0;
    for i=2:H-1     
        for j=2:W-1      
            Gx=(U(i 1,j-1) 2*U(i 1,j) F(i 1,j 1))-(U(i-1,j-1) 2*U(i-1,j) F(i-1,j 1));
            Gy=(U(i-1,j 1) 2*U(i,j 1) F(i 1,j 1))-(U(i-1,j-1) 2*U(i,j-1) F(i 1,j-1));    
            uSobel(i,j)=sqrt(Gx^2 Gy^2);
            %    ms=ms uSobel(i,j); 
            %   ns=ns (uSobel(i,j)-ms)^2;     
        end
    end
    %     ms=ms/(H*W); 
    %     ns=ns/(H*W);
    imshow(M);  
    figure;
    imshow(im2uint8(uSobel));title('Sobel处理后');
    for i=1:H
        for j=1:W
            if(uSobel(i,j)<150)
                uSobel(i,j)=0;
            else
                uSobel(i,j)=1;
            end
        end
    end
    uSobel=mat2gray(uSobel);
    figure;imshow(uSobel);title('阈值细化');

    
    
% hObject    handle to pushbutton10 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton12.
function pushbutton12_Callback(hObject, eventdata, handles)
    [filename, pathname] = uigetfile('*.jpg', '读取图片文件'); %选择图片文件
    if isequal(filename,0)   %判断是否选择
       msgbox('没有选择任何图片');
    else
       pathfile=fullfile(pathname, filename);  %获得图片路径
       global  M;
       M=imread(pathfile);     %将图片读入矩阵
       imshow(M);
    end
% hObject    handle to pushbutton12 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


% --- Executes on button press in pushbutton13.
function pushbutton13_Callback(hObject, eventdata, handles)
       button13=questdlg('你确定退出吗？','退出程序','Yes','No','Yes');
       if strcmp(button13,'Yes')
       close all;
       end;

    
    
% hObject    handle to pushbutton13 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)


function d=image_gray(src)
    ima_red=src(:,:,1);
    ima_green=src(:,:,2);
    ima_blue=src(:,:,3);
    d=0.299*ima_red 0.587*ima_green 0.114*ima_blue;

    
    
    
function desimg=image_gaussian(originimg,sigma,N)  
    [ori_row,ori_col]=size(originimg);
    N_row = 2*N 1;  
    
    H = [];%求高斯模板H  
    for i=1:N_row  
        for j=1:N_row  
            fenzi=double((i-N-1)^2 (j-N-1)^2);  
            H(i,j)=exp(-fenzi/(2*sigma*sigma))/(2*pi*sigma);  
        end  
    end  
    H=H/sum(H(:));%归一化  
    
    temp=[];             %模板与图像卷积实现
    desimg=[ori_row,ori_col];
    for ai=N 1:ori_row-N-1  
        for aj=N 1:ori_col-N-1  
            temp=0;  
            for bi=1:N_row  
                for bj=1:N_row  
                    temp= temp (originimg(ai bi-N,aj bj-N)*H(bi,bj));  
                end  
            end  
            desimg(ai,aj)=temp;  
        end  
    end  
    desimg=uint8(desimg);  


function re=get_coords(angle)       %angle是边缘法线角度，返回法线前后两点
    sigma=0.000000001;
    x1=ceil(cos(angle pi/8)*sqrt(2)-0.5-sigma);
    y1=ceil(-sin(angle-pi/8)*sqrt(2)-0.5-sigma);
    x2=ceil(cos(angle-pi/8)*sqrt(2)-0.5-sigma);
    y2=ceil(-sin(angle-pi/8)*sqrt(2)-0.5-sigma);
    re=[x1 y1 x2 y2];



function nedge=connect(nedge,y,x,low)       %种子定位后的连通分析
    neighbour=[-1 -1;-1 0;-1 1;0 -1;0 1;1 -1;1 0;1 1];  %八连通搜寻
    [m n]=size(nedge);
    for k=1:8
        yy=y neighbour(k,1);
        xx=x neighbour(k,2);
        if yy>=1 &&yy<=m &&xx>=1 && xx<=n  
            if nedge(yy,xx)>=low && nedge(yy,xx)~=255   %判断下阈值
                nedge(yy,xx)=255;
                nedge=connect(nedge,yy,xx,low);
            end
        end        
    end 
    
    function d=mid_filter(ima,N)     
    [height, width]=size(ima);   %输入图像是p×q的,且p>n,q>n  
    x1=double(ima);  
    x2=x1; 
    for i=1:height-N 1  
        for j=1:height-N 1  
            c=x1(i:i (N-1),j:j (N-1)); %取出x1中从(i,j)开始的n行n列元素,即模板(n×n的)  
            e=c(1,:);      %是c矩阵的第一行  
            for u=2:N  
                e=[e,c(u,:)];     %将c矩阵变为一个行矩阵      
            end  
            mm=median(e);      %mm是中值  
            x2(i round((N-1)/2),j round((N-1)/2))=mm;   %将模板各元素的中值赋给模板中心位置的元素  
        end  
    end   
    d=uint8(x2);     %未被赋值的元素取原值  
    
    function d=avg_filter(image,n)     
    a(1:n,1:n)=1;   %a即n×n模板,元素全是1  
    [height, width]=size(image);   %输入图像是hightxwidth的,且hight>n,width>n  
    x1=double(image);  
    x2=x1;  
    for i=1:height-n 1  
        for j=1:width-n 1  
            c=x1(i:i (n-1),j:j (n-1)).*a; %取出x1中从(i,j)开始的n行n列元素与模板相乘  
            s=sum(sum(c));                 %求c矩阵中各元素之和  
            x2(i (n-1)/2,j (n-1)/2)=s/(n*n); %将与模板运算后的各元素的均值赋给模板中心位置的元素  
        end  
    end  
    %未被赋值的元素取原值  
    d=uint8(x2); 

function B=low_pass_filter(image)
    m=double(image); 
    f=fft2(m); 
    f=fftshift(f);  
    [N1,N2]=size(f);  %返回矩阵的行和列 
    n1=round(N1/2); 
    n2=round(N2/2);  
    n=2;d0=50; %滤波器截止频率,滤波半径 
    for i=1:N1    
        for j=1:N2         
            d=sqrt((i-n1)^2 (j-n2)^2);        %计算低通滤波转换函数        
            if d<=d0              
                h=1;        
            else
                h=0;
            end
            y(i,j)=h*f(i,j);    
        end
    end
    y=ifftshift(y);
    A=ifft2(y); 
    B=uint8(real(A));  

function nk=histogram(image)
    L=256; %灰度级 
    nk=zeros(L,1);%出现次数
    [row,col]=size(image);
    n=row*col; %总像素个数
    for i = 1:row
    for j = 1:col
    num = double(image(i,j)) 1; %获取像素点灰度级0到255所以要加上1
    nk(num) = nk(num) 1; %统计nk 
    end
    end