function varargout = test(varargin)
% TEST MATLAB code for test.fig
% TEST, by itself, creates a new TEST or raises the existing
% singleton*.
%
% H = TEST returns the handle to a new TEST or the handle to
% the existing singleton*.
%
% TEST('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in TEST.M with the given input arguments.
%
% TEST('Property','Value',...) creates a new TEST or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before test_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to test_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 test
% Last Modified by GUIDE v2.5 27-Jun-2023 17:12:12
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @test_OpeningFcn, ...
'gui_OutputFcn', @test_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end
mainfc;
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 test is made visible.
function test_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 test (see VARARGIN)
% Choose default command line output for test
handles.output = hObject;
mainfc;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes test wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = test_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)
[filename, pathname] = uigetfile({'*.jpg';'*.bmp';'*.jpeg'},'选择图像');
if isequal(filename,0) | isequal(pathname,0)
disp('取消，重选');
else
disp(['选择 ', fullfile(pathname, filename)])
end
x=imread(filename);
axes(handles.axes1)
imshow(x)
title('原图')
handles.x=x
guidata(hObject, handles);
set(handles.text2,'string','图像选择完毕')
% 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)
set(handles.text2,'string','梯度倒数加权平均平滑算法。。。')
pause(1)
tic
x=handles.x
I=x;
H=sqrt(double(I));%把数据类型转换成double,然后进行平方根变换
H=uint8(H);%sqrt函数不支持uint8类型,把数据类型转换成uint8类型
%对图象p1-03施加高斯噪声和椒盐噪声并实施梯度倒数加权平滑法（公式4.2.3、4.2.4、4.2，利用方差评价空域平滑的效果
a=imnoise(I,'salt & pepper');
axes(handles.axes2); imshow(a); title('椒盐噪声图');
a=double(a);
[dep,wide]=size(a);
new_image=ones(size(a));
r=0.5;
for i=2:dep-1
for j=2:wide-1
g=0;
for m=-1:1
for n=-1:1
if(a(i+m,j+n)-a(i,j)==0)
g(m+2,n+2)=0;
else
g(m+2,n+2)=1/abs(a(i+m,j+n)-a(i,j));
end
end
end
G=sum(sum(g));
for m=-1:1
for n=-1:1
w(m+2,n+2)=g(m+2,n+2)/G;
end
end
new_image(i,j)=a(i,j)*r+(1-r)*(w(-1+2,-1+2)*a(i-1,j-1)+w(-1+2,0+2)*a(i-1,j)+w(-1+2,1+2)*a(i-1,j+1)+w(0+2,-1+2)*a(i,j-1)+w(0+2,1+2)*a(i,j+1)+w(1+2,-1+2)*a(i+1,j-1)+w(1+2,0+2)*a(i+1,j)+w(1+2,1+2)*a(i+1,j+1));
end
end
for i=2:dep-1
new_image(i,1)=new_image(i,2);
new_image(i,wide)=new_image(i,wide-1);
end
new_image(1,:)=new_image(2,:);
new_image(dep,:)=new_image(dep-1,:);
axes(handles.axes3); imshow(x); title('最后梯度倒数加权平滑');
time=toc
set(handles.edit1,'string',time)
set(handles.text2,'string','梯度倒数加权平均平滑处理完毕')
% 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)
set(handles.text2,'string','最大均匀性平滑滤波开始,约需等待95s。。。')
pause(1)
tic
x=handles.x
%**********************最大均匀性平滑法滤波*************************%
im=x;
[m,n]=size(im);
noise_pic=imnoise(im,'salt & pepper',0.02);
axes(handles.axes2)
imshow(noise_pic);
title('椒盐噪声图')
I=im2double(im) ;
for h=1:m
X(1,h)=I(1,h);
X(2,h)=I(2,h);
X(n-1,h)=I(n-1,h);
X(n,h)=I(n,h);
end
for j=1:n
X(j,1)=I(j,1);
X(j,2)=I(j,2);
X(j,m-1)=I(j,m-1);
X(j,m)=I(j,m);
end
for i=3:n-2
for j=3:m-2
F1=[I(i-2,j-2),I(i-2,j-1),I(i-2,j),I(i-1,j-2),I(i-1,j-1),I(i-1,j),I(i,j-2),I(i,j-1),I(i,j)];%取出每个邻域的像素值
F2=[I(i-2,j+1),I(i-2,j-1),I(i-2,j),I(i-1,j+1),I(i-1,j-1),I(i-1,j),I(i,j+1),I(i,j-1),I(i,j)];
F3=[I(i-2,j+1),I(i-2,j+2),I(i-2,j),I(i-1,j+1),I(i-1,j+2),I(i-1,j),I(i,j+1),I(i,j+2),I(i,j)];
F4=[I(i+1,j-2),I(i+1,j-1),I(i+1,j),I(i-1,j-2),I(i-1,j-1),I(i-1,j),I(i,j-2),I(i,j-1),I(i,j)];
F5=[I(i+1,j+1),I(i+1,j-1),I(i+1,j),I(i-1,j+1),I(i-1,j-1),I(i-1,j),I(i,j+1),I(i,j-1),I(i,j)];
F6=[I(i+1,j+1),I(i+1,j+2),I(i+1,j),I(i-1,j+1),I(i-1,j+2),I(i-1,j),I(i,j+1),I(i,j+2),I(i,j)];
F7=[I(i+1,j-2),I(i+1,j-1),I(i+1,j),I(i+2,j-2),I(i+2,j-1),I(i+2,j),I(i,j-2),I(i,j-1),I(i,j)];
F8=[I(i+1,j+1),I(i+1,j-1),I(i+1,j),I(i+2,j+1),I(i+2,j-1),I(i+2,j),I(i,j+1),I(i,j-1),I(i,j)];
F9=[I(i+1,j+1),I(i+1,j+2),I(i+1,j),I(i+2,j+1),I(i+2,j+2),I(i+2,j),I(i,j+1),I(i,j+2),I(i,j)];
I1=var(F1);
I2=var(F2);
I3=var(F3);
I4=var(F4);
I5=var(F5);
I6=var(F6);
I7=var(F7);
I8=var(F8);
I9=var(F9); %求方差
array=[I1,I2,I3,I4,I5,I6,I7,I8,I9]; %将方差放在一个数组中
A=sort(array); %对方差排序
switch A(1) %判断最小方差属于哪一个邻域
case I1
average=(I(i-2,j-2)+I(i-2,j-1)+I(i-2,j)+I(i-1,j-2)+I(i-1,j-1)+I(i-1,j)+I(i,j-2)+I(i,j-1)+I(i,j))/9;
case I2
average=(I(i-2,j+1)+I(i-2,j-1)+I(i-2,j)+I(i-1,j+1)+I(i-1,j-1)+I(i-1,j)+I(i,j+1)+I(i,j-1)+I(i,j))/9;
case I3
average=(I(i-2,j+1)+I(i-2,j+2)+I(i-2,j)+I(i-1,j+1)+I(i-1,j+2)+I(i-1,j)+I(i,j+1)+I(i,j+2)+I(i,j))/9;
case I4
average=(I(i+1,j-2)+I(i+1,j-1)+I(i+1,j)+I(i-1,j-2)+I(i-1,j-1)+I(i-1,j)+I(i,j-2)+I(i,j-1)+I(i,j))/9;
c
