⛄一、获取代码方式

获取代码方式1：
完整代码已上传我的资源：【图像增强】基于matlab GUI retinex图像增强（SSR,MSR.MSRCR,MSRCP）【含Matlab源码 4650期】
点击上面蓝色字体，直接付费下载，即可。

获取代码方式2：
付费专栏Matlab图像处理（初级版）

备注：
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点击CSDN资源下载链接：1份本博客上传CSDN资源代码

⛄二、retinex图像增强（SSR,MSR.MSRCR,MSRCP）

Retinex图像增强是一种基于对数域的图像增强方法，通过对图像进行多次分解和重建，以增强图像的对比度和色彩平衡，从而改善图像的质量。常见的Retinex图像增强算法包括SSR、MSR、MSRCR和MSRCP。

其中，SSR算法（Single-Scale Retinex）使用高斯核函数对图像进行滤波，并将原始图像与滤波后的图像相除，得到反射率图像。然后使用对数域变换对反射率图像进行增强，最后将增强后的反射率图像与原始图像相乘得到增强后的图像。

MSR算法（Multi-Scale Retinex）将原始图像进行多次高斯滤波，得到不同尺度下的图像。然后对每个尺度的图像进行Retinex增强，得到反射率图像。最后将不同尺度下的反射率图像加权平均得到最终的反射率图像，再进行对数域变换和乘法运算得到增强后的图像。

MSRCR算法（Multi-Scale Retinex with Color Restoration）在MSR算法的基础上加入了颜色恢复步骤，通过对彩色图像的颜色信息进行保护，避免了增强过程中产生的颜色偏移。

MSRCP算法（Multi-Scale Retinex with Color Preservation）在MSRCR算法的基础上进一步加入了颜色保护步骤，通过对颜色通道进行归一化处理，避免了颜色失真现象。

⛄三、部分源代码

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

% Last Modified by GUIDE v2.5 06-Jun-2024 23:17:50

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct(‘gui_Name’, mfilename, …
‘gui_Singleton’, gui_Singleton, …
‘gui_OpeningFcn’, @main_OpeningFcn, …
‘gui_OutputFcn’, @main_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 main is made visible.
function main_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 main (see VARARGIN)

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

% Update handles structure
guidata(hObject, handles);

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

% — Outputs from this function are returned to the command line.
function varargout = main_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 axes1_CreateFcn(hObject, eventdata, handles)
% hObject handle to axes1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: place code in OpeningFcn to populate axes1

% — 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)
%[filename,pathname]=uigetfile({‘.jpg’;'.bmp’,‘.png’},‘Choose File’);
%[FileName,PathName] = uigetfile({'.m’;‘.slx’;'.mat’;‘.png’;'.jpg’},‘Select the MATLAB code file’);
[filename, pathname, filterindex] = uigetfile({‘.png’;'.jpg’},‘Pick a image’)
%
handles.myImage = strcat(pathname, filename);
gg=strcat(pathname, filename);
axes(handles.axes1);
imshow(handles.myImage);
Code(gg);

⛄四、运行结果

⛄五、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1]恩铭,杨松,姚志强,骆成军.基于CNN模型的椒盐噪声图像的分类[J].新乡学院学报. 2022,39(03)

3 备注
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