function varargout = CLPI(varargin)
% CLPI M-file for CLPI.fig
% CLPI, by itself, creates a new CLPI or raises the existing
% singleton*.
%
% H = CLPI returns the handle to a new CLPI or the handle to
% the existing singleton*.
%
% CLPI('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in CLPI.M with the given input arguments.
%
% CLPI('Property','Value',...) creates a new CLPI or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before CLPI_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to CLPI_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 CLPI
% Last Modified by GUIDE v2.5 18-May-2017 14:42:35
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @CLPI_OpeningFcn, ...
'gui_OutputFcn', @CLPI_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 CLPI is made visible.
function CLPI_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 CLPI (see VARARGIN)
% Choose default command line output for CLPI
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes CLPI wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = CLPI_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)
global im
[filename,pathname]=uigetfile({'*.jpg';'*.bmp';'*.tif'},'选择照片');
str=[pathname,filename];
im=imread(str);
axes(handles.axes1);
imshow(im)
% --- 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)
global im
im2 = im(end:-1:1,:,:);%垂直翻转
im3 = im(:,end:-1:1,:);%水平翻转
im4 = im(end:-1:1,end:-1:1,:);%对角翻转
if size(im,3)==1
im5 = medfilt2(im,[3,2]);
else
im51=medfilt2(im(:,:,1),[3,2]);%R通道滤波
im52=medfilt2(im(:,:,2),[3,2]);%R通道滤波
im53=medfilt2(im(:,:,3),[3,2]);%R通道滤波
im5=cat(3,im51,im52,im53);%中值滤波后的图像
end
axes(handles.axes2);
imshow(im5)
% --- 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)
global im imgysw imgray
%{
img = im;
img_1=img(:,:,1);
img_2=img(:,:,2);
img_3=img(:,:,3);
Y=0.299*img_1+0.587*img_2+0.114*img_3;%平衡系数
[m,n]=size(Y);
k=Y(1,1);
for i=1:m
for j=1:n
if Y(i,j)>=k
k=Y(i,j);
k1=i;
k2=j;
end
end
end
[m1,n1]=find(Y==k);
Rave=sum(sum(img_1));
Rave=Rave/(m*n);
Gave=sum(sum(img_2));
Gave=Gave/(m*n);
Bave=sum(sum(img_3));
Bave=Bave/(m*n);
Kave=(Rave+Gave+Bave)/3;
img_1=(Kave/Rave)*img_1;
img_2=(Kave/Gave)*img_2;
img_3=(Kave/Bave)*img_3;
imgysw=cat(3,img_1,img_2,img_3);
axes(handles.axes2);
imshow(imgysw)
%}
imgray = rgb2gray(im);
axes(handles.axes2);
imshow(imgray)
% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
% 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)
warning off
feature jit off
global im im_noise
im_noise=imnoise(im,'salt & pepper',0.05);
axes(handles.axes2);
imshow(im_noise)
% --- Executes on button press in pushbutton5.
function pushbutton5_Callback(hObject, eventdata, handles)
% 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)
warning off
feature jit off
global im_noise im_filter
n=size(size(im_noise));
if n(1,2)==2
im_filter=medfilt2(im_noise,[3,2]);
else
im_filter1=medfilt2(im_noise(:,:,1),[3,2]);
im_filter2=medfilt2(im_noise(:,:,2),[3,2]);
im_filter3=medfilt2(im_noise(:,:,3),[3,2]);
im_filter=cat(3,im_filter1,im_filter2,im_filter3);
end
axes(handles.axes2);
imshow(im_filter)
% --- Executes on button press in pushbutton6.
function pushbutton6_Callback(hObject, eventdata, handles)
% 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)
warning off
feature jit off
global im_noise im_filter imgysw Plate Plate2 Plate2s
[Path] = uigetdir('','保存的图像');
%imwrite(uint8(im_filter),strcat(Path,'\','pic_correct.bmp'),'bmp');
imwrite(uint8(Plate2s),strcat(Path,'\','pic_correct.bmp'),'bmp');
% --- Executes on button press in pushbutton7.
function pushbutton7_Callback(hObject, eventdata, handles)
% 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)
global im im_noise imgysw imgray
axes(handles.axes2);
BW=edge(imgray,'sobel',0.08);
imshow(BW)
% --- Executes on button press in pushbutton8.
function pushbutton8_Callback(hObject, eventdata, handles)
% 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)
global im im_noise imgysw im_filter imgray
axes(handles.axes2);
BW=edge(imgray,'prewitt');
imshow(BW)
% --- Executes on button press in pushbutton9.
function pushbutton9_Callback(hObject, eventdata, handles)
% 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)
global im im_noise imgysw imgray
axes(handles.axes2);
BW=edge(imgray,'canny');
imshow(BW)
% --- Executes on button press in pushbutton10.
function pushbutton10_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton10 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles
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仿真是一种利用计算机模型复现实际系统并对其进行实验研究的技术手段。通过建立数学或物理模型来模拟真实世界的系统,并通过实验对它们进行分析和优化。仿真技术在多个领域发挥着重要作用,包括航空航天、军事、工业、经济等。 仿真技术的发展始于20世纪初,最初应用于水利模型研究和实验室工作。随着计算机技术的进步,仿真技术得到了快速发展。尤其是在50年代至60年代,仿真技术广泛应用于航空、航天和原子能等领域,大大推动了其技术进步。 仿真技术主要依赖于计算机硬件和软件。用于仿真的计算机类型包括模拟计算机、数字计算机和混合计算机。仿真软件则涵盖了仿真程序、程序包、语言以及数据库管理系统,如SimuWorks平台,它提供了从建模、实时运行到结果分析的全过程支持。 仿真方法可以分为两大类:连续系统的仿真方法和离散事件系统的仿真方法。连续系统仿真通常涉及常微分方程或偏微分方程,而离散事件系统仿真则关注随机时间点的状态变化,主要用于统计特性分析。 总的来说,仿真技术通过模拟现实世界的各种系统,帮助人们更好地理解、预测和优化这些系统的性能。未来,随着技术的不断进步,仿真将在更多领域发挥更大的作用,为科学研究和技术发展提供强有力的支持。
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