【图像去噪】基于最小二乘方滤波实现图像去噪含Matlab源码

 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

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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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