【图像压缩】基于小波变换图像压缩含Matlab源码.zip

【图像压缩】基于小波变换图像压缩含Matlab源码

1 简介

数字图像压缩技术是使用最少的数据信息表示原图像的一种信息处理技术.本文先从小波变换的分解与重

构分析原理入手,使用基于Matlab的小波变换算法进行数字图像压缩处理,获取较大的图像压缩比,处理后

的图像清晰度高、效果好.

2 部分代码

function varargout = multi_wavelet(varargin)



'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{:});

% 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 multi_wavelet (see VARARGIN)



% Choose default command line output for multi_wavelet

handles.output = hObject;



% Update handles structure

% --- Outputs from this function are returned to the command line.

function varargout = multi_wavelet_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;

% handles structure with handles and user data (see GUIDATA)

global I ;

[fname,pname]=uigetfile('.');

I=imread(strcat(pname,'',fname));

[m,n,k]=size(I);

if k~=1

I=rgb2gray(I);

end

I=double(I);

axes(handles.axes1);

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)



% Hints: contents = get(hObject,'String') returns popupmenu1 contents as cell array

% contents{get(hObject,'Value')} returns selected item from popupmenu1



global I ;