function gaussian_Callback(hObject, eventdata, handles) % hObject handle to gaussian (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global T axes(handles.axes2); T=getimage; p=inputdlg({'噪声方差为:'},'输入',1,{'0.05'}); if isempty(p)==1 %errordlg('没有输入！','error'); return else p=str2num(p{1}); I=imnoise(T,'gaussian',0,p); %添加白噪声，其平均值为0，方差为0.05 imshow(I); end

这是一个 MATLAB GUI 中的回调函数，用于在 GUI 界面上添加高斯白噪声到图像中，并显示添加噪声后的图像。

函数的基本流程如下：

1. 获取当前 GUI 界面中的图像 T，使用 `getimage` 函数获取。
2. 弹出输入对话框，让用户输入噪声方差 p。
3. 如果用户没有输入，则直接返回；否则将用户输入转换为数值类型。
4. 使用 `imnoise` 函数向图像中添加高斯白噪声，噪声的均值为0，方差为 p。
5. 在 GUI 界面的 axes2 中显示添加噪声后的图像，使用 `imshow` 函数。

需要注意的是，该函数中使用了 `global` 关键字，表示 T 和 axes2 是全局变量，可以在其他函数中访问。函数中使用了 `inputdlg` 函数弹出对话框，让用户输入噪声方差。同时，函数中调用了 `imnoise` 函数向图像中添加高斯白噪声，并使用 `imshow` 函数在界面上显示添加噪声后的图像。

相关问题

%高斯噪声 % --- Executes on button press in pushbutton12. function pushbutton12_Callback(hObject, eventdata, handles) % 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) global bw_invert noisy = imnoise(bw_invert, 'gaussian', 0, 0.01); axes(handles.axes2); cla; imshow(noisy); guidata(hObject,handles);

这段MATLAB代码实现了一个名为"高斯噪声"的按钮的回调函数。当用户点击这个按钮时，它会将全局变量bw_invert所对应的二值图像添加高斯噪声，并在GUI界面上的axes2中显示噪声图像。

imnoise函数的第一个参数bw_invert是输入的二值图像，'gaussian'表示添加高斯噪声，0表示噪声的均值，0.01表示噪声的方差。最后使用imshow函数在axes2中显示添加噪声后的图像。

这段代码中使用了MATLAB的全局变量，因此需要在其他地方定义和初始化bw_invert变量。例如：

global bw_invert;
bw = imread('binary_image.bmp');
bw_invert = imcomplement(im2bw(bw));

这段代码中，我们首先读取一个二值图像，然后使用imcomplement函数进行二值图像的反转，再使用im2bw函数将图像转换为二值图像，并将其赋值给全局变量bw_invert。这样，在高斯噪声按钮的回调函数中就可以直接使用bw_invert变量了。

function slider2_Callback(hObject, eventdata, handles) % hObject handle to slider2 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'Value') returns position of slider % get(hObject,'Min') and get(hObject,'Max') to determine range of slider global im; % 提示：get（hObject，'Value'）返回滑块的位置 a=get(handles.slider2,'value'); x1=imadjust(im,[0.3 0.7],[0 1],a); axes(handles.axes2); imshow(x1); % --- Executes during object creation, after setting all properties. function slider2_CreateFcn(hObject, eventdata, handles) % hObject handle to slider2 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: slider controls usually have a light gray background. if isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor',[.9 .9 .9]); end 像这样写一个调节高斯噪声强度的matlab GUI代码

好的，以下是一个简单的 MATLAB GUI 代码，可以通过滑动调节高斯噪声的强度：

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

% Last Modified by GUIDE v2.5 16-Aug-2021 23:06:41

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

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

% Update handles structure
guidata(hObject, handles);

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

% Load sample image
handles.im = imread('peppers.png');
axes(handles.axes1);
imshow(handles.im);
title('Original Image');

% Set slider range and default value
set(handles.slider1, 'Min', 0);
set(handles.slider1, 'Max', 1);
set(handles.slider1, 'Value', 0.1);

% Call slider1_Callback to apply initial Gaussian noise
slider1_Callback(handles.slider1, eventdata, handles);


% --- Outputs from this function are returned to the command line.
function varargout = GaussianNoiseGUI_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 slider movement.
function slider1_Callback(hObject, eventdata, handles)
% hObject    handle to slider1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Apply Gaussian noise to image
handles.a = get(handles.slider1, 'Value');
handles.im_noisy = imnoise(handles.im, 'gaussian', 0, handles.a);
axes(handles.axes2);
imshow(handles.im_noisy);
title(['Gaussian Noise (Intensity = ' num2str(handles.a) ')']);

% Update handles structure
guidata(hObject, handles);


% --- Executes during object creation, after setting all properties.
function slider1_CreateFcn(hObject, eventdata, handles)
% hObject    handle to slider1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: slider controls usually have a light gray background.
if isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor',[.9 .9 .9]);
end

这个 GUI 包含两个 axes 对象，一个用于显示原始图像，另一个用于显示加了高斯噪声的图像。代码中的 `imread('peppers.png')` 可以替换为你自己的图像文件名或路径。

在 `GaussianNoiseGUI_OpeningFcn` 中，我们加载了一个示例图像 `peppers.png`，并设置了 `slider1` 的范围和默认值。我们还调用了 `slider1_Callback` 函数，以便在打开 GUI 时应用默认的高斯噪声。

在 `slider1_Callback` 函数中，我们通过 `imnoise` 函数向图像中添加高斯噪声，然后将其显示在 `axes2` 中。我们还更新了 `handles` 结构体中的 `a` 和 `im_noisy` 变量，以便在其他函数中访问和使用它们。

最后，我们还提供了一个 `slider1_CreateFcn` 函数，用于设置 `slider1` 的背景颜色。