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【图像去噪】基于最小二乘方滤波实现图像去噪含Matlab源码

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【图像去噪】基于最小二乘方滤波实现图像去噪含Matlab源码

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1 简介

基于最小二乘方滤波实现图像去噪含Matlab源码

2 部分代码

function varargout = zuixiaoercheng(varargin) % ZUIXIAOERCHENG M-file for zuixiaoercheng.fig % ZUIXIAOERCHENG, by itself, creates a new ZUIXIAOERCHENG or raises the existing % singleton*. % % H = ZUIXIAOERCHENG returns the handle to a new ZUIXIAOERCHENG or the handle to % the existing singleton*. % % ZUIXIAOERCHENG(’CALLBACK’,hObject,eventData,handles,...) calls the local % function named CALLBACK in ZUIXIAOERCHENG.M with the given input arguments. % % ZUIXIAOERCHENG(’Property’,’Value’,...) creates a new ZUIXIAOERCHENG or raises the % existing singleton*. Starting from the left, property value pairs are % applied to the GUI before zuixiaoercheng_OpeningFunction gets called. An % unrecognized property name or invalid value makes property application % stop. All inputs are passed to zuixiaoercheng_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 zuixiaoercheng % Last Modified by GUIDE v2.5 20-May-2009 15:56:50 % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct(’gui_Name’, mfilename, ... ’gui_Singleton’, gui_Singleton, ... ’gui_OpeningFcn’, @zuixiaoercheng_OpeningFcn, ... ’gui_OutputFcn’, @zuixiaoercheng_OutputFcn, ... ’gui_LayoutFcn’, [] , ... ’gui_Callback’, []); if nargin & isstr(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 zuixiaoercheng is made visible. function zuixiaoercheng_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 zuixiaoercheng (see VARARGIN) img = imread(’squarebox.bmp’); axes(handles.axes1); imshow(img); PSF = fspecial(’motion’,20,45); MF = imfilter(img,PSF,’circular’); noise = imnoise(zeros(size(img)),’gaussian’,0,0.01); MF = double(MF); MFN = MF+noise; axes(handles.axes2); imshow(uint8(MFN)); fr = deconvreg(MFN,PSF,4,[1e-7,1e7]); axes(handles.axes3); imshow(uint8(fr)); set(handles.noisepower_edit,’string’,4); % Choose default command line output for zuixiaoercheng handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes zuixiaoercheng wait for user response (see UIRESUME) % uiwait(handles.zuixiaoercheng); % --- Outputs from this function are returned to the command line. function varargout = zuixiaoercheng_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 during object creation, after setting all properties. function image_pop_menu_CreateFcn(hObject, eventdata, handles) % hObject handle to image_pop_menu (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: popupmenu controls usually have a white background on Windows. % See ISPC and COMPUTER. if ispc set(hObject,’BackgroundColor’,’white’); else set(hObject,’BackgroundColor’,get(0,’defaultUicontrolBackgroundColor’)); end % --- Executes on selection change in image_pop_menu. function image_pop_menu_Callback(hObject, eventdata, handles) % hObject handle to image_pop_menu (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) noisepower = str2num(get(handles.noisepower_edit,’string’)); val = get(hObject,’value’); str = get(hObject,’string’); switch str{val} case ’Squarebox’ squarebox = []; squarebox = imread(’squarebox.bmp’); img = squarebox; case ’Lena’ lena = []; lena = imread(’lena.bmp’); img = lena; case ’Saturn’ saturn = []; load imdemos saturn img = saturn; case ’Quarter’ quarter = []; load imdemos quarter img = quarter; case ’Circuit’ circuit = []; load imdemos circuit img = circuit; case ’Fingerprint’ fingerprint = []; fingerprint = imread(’fingerprint.jpg’); img = fingerprint; case ’Licenceplate’ licenceplate = []; licenceplate = imread(’licenceplate.jpg’); img = licenceplate; case ’Cloudy’ cloudy = []; cloudy = imread(’cloudy.tif’); img = cloudy; end axes(handles.axes1); imshow(img); PSF = fspecial(’motion’,20,45); MF = imfilter(img,PSF,’circular’); noise = imnoise(zeros(size(img)),’gaussian’,0,0.01); MF = double(MF); MFN = MF+noise; axes(handles.axes2); imshow(uint8(MFN)); fr = deconvreg(MFN,PSF,noisepower,[1e-7,1e7]); axes(handles.axes3); imshow(uint8(fr));

3 仿真结果

4 参考文献

[1]张然, 汤全武, 史崇升. 基于递推最小二乘自适应滤波算法的图像去噪[J]. 计算机应用与软件, 2014(4):193-196.

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