【图像去噪】基于matlab GUI中值+均值+维纳+小波滤波图像去噪【含Matlab源码 800期】
作者：互联网
一、简介
基于matlab GUI中值+均值+维纳+小波滤波图像去噪
二、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 20-Apr-2021 22:48:39
% 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 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)
%% 读取图像
[filename, pathname] = uigetfile(...
{'*.bmp;*.jpg; *.png; *.jpeg; ','Image Files(*.bmp,*.jpg,*.png,*.jpeg)';...
'*.*', 'All Files(*.*)' }...
, 'Pick an image');%打开文件 选择图像
if isequal(filename,0) || isequal(pathname,0)
return;%如 果点了“ 取 消”
end
axes(handles.axes1);%重要，在哪个坐标轴显示图像
fpath = [pathname filename];%路径名和文件名
img1 = imread(fpath);%读取图像
imshow(img1);%显示图像
handles.img1=img1;
title('原图')
guidata(hObject, handles);
% --- Executes on button press in pushbutton2.
function pushbutton2_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
%% 高斯噪声
img1=handles.img1;
img2 = imnoise(img1,'gaussian'); %加高斯噪声
axes(handles.axes2);
imshow(img2);
handles.img2=img2;
title('高斯噪声图')
guidata(hObject, handles);
function [zipped, info] = huffencode(vector)
% 输入和输出都是 uint8 格式
% info 返回解码需要的结构信息
% info.pad 是添加的比特数
% info.huffcodes 是 Huffman 码字
% info.rows 是原始图像行数
% info.cols 是原始图像列数
% info.length 是原始图像数据长度
% info.maxcodelen 是最大码长
if ~isa(vector, 'uint8')
error('input argument must be a uint8 vector');
end
[m, n] = size(vector);
vector = vector(:)';%
f = frequency(vector); %计算各符号出现的概率
symbols = find(f~=0);
f = f(symbols);
[f, sortindex] = sort(f); %将符号按照出现的概率大小排列
symbols = symbols(sortindex);
len = length(symbols);
symbols_index = num2cell(1:len);
codeword_tmp = cell(len, 1);
% 生成 Huffman 树，得到码字编码表
while length(f)>1
index1 = symbols_index{1};
index2 = symbols_index{2};
codeword_tmp(index1) = addnode(codeword_tmp(index1), uint8(0));
codeword_tmp(index2) = addnode(codeword_tmp(index2), uint8(1));
f = [sum(f(1:2)),f(3:end)];
symbols_index = [{[index1, index2]},symbols_index(3:end)];
[f, sortindex] = sort(f);
symbols_index = symbols_index(sortindex);
end
codeword = cell(256, 1);
codeword(symbols) = codeword_tmp;
len = 0;
for index = 1:length(vector) %得到整个图像所有比特数
len = len + length(codeword{double(vector(index))+1});
end
string = repmat(uint8(0), 1, len);
pointer = 1;
for index = 1:length(vector) %对输入图像进行编码
code = codeword{double(vector(index))+1};
len = length(code);
string(pointer + (0:len-1))=code;
pointer = pointer + len;
end
len = length(string);
pad = 8-mod(len, 8);
if pad > 0
string = [string uint8(zeros(1, pad))];
end
codeword = codeword(symbols);
codelen = zeros(size(codeword));
weights = 2.^(0:23);
maxcodelen = 0;
for index = 1:length(codeword)
len = length(codeword{index});
if len > maxcodelen;
maxcodelen = len;
end
if len > 0
code = sum(weights(codeword{index} == 1));
code = bitset(code, len + 1);
codeword{index} = code;
codelen(index) = len;
end
end
codeword = [codeword{:}];
%计算压缩的向量
cols = length(string)/8;
string = reshape(string, 8, cols);
weights = 2.^(0: 7);
zipped = uint8(weights * double(string));
%码表存储到一个希疏矩阵
huffcodes = sparse(1, 1);
for index = 1:nnz(codeword) % length(codeword) %numel(codeword)
huffcodes(codeword(index), 1) = symbols(index);
end
%填写解码时所需的结构信息
info.pad = pad;
info.huffcodes = huffcodes;
info.ratio = cols./length(vector);
info.length = length(vector);
info.maxcodelen = maxcodelen;
info.rows = m;
info.cols = n;
%函数addnode添加节点
function codeword_new = addnode(codeword_old, item)
codeword_new = cell(size(codeword_old));
for index = 1:length(codeword_old)
codeword_new{index} = [item codeword_old{index}];
end
%函数frequency计算各符号出现的概率
function f = frequency(vector)
if ~isa(vector, 'uint8')
error('input argument must be a uint8 vector');
end
f = repmat(0, 1, 256);
len = length(vector);
for index = 0:255
f(index+1) = sum(vector == uint8(index));
end
f = f./len; %归一化
function y = jpegencode(x, quality)
%jpegencode函数用来压缩图像，x为输入图像
%quality决定了截去的系数和压缩比
error(nargchk(1, 2, nargin)); %检查输入参数
if nargin < 2
quality = 1; %默认时 quality为1
end
x = double(x) - 128; %像素层次移动-128
[xm, xn] = size(x); %得到像素尺寸
t = dctmtx(8); %得到8*8DCT矩阵
%将图像分割成8*8子图像，进行DCT，然后进行量化
y = blkproc(x, [8,8], 'P1*x*P2', t, t');%
m = [16 11 10 16 24 40 51 61 %JPEG量化步长矩阵
12 12 14 19 26 58 60 55
14 13 16 24 40 57 69 56
14 17 22 29 51 87 80 62
18 22 37 56 68 109 103 77
24 35 55 64 81 104 113 92
49 64 78 87 103 121 120 101
72 92 95 98 112 110 103 99]*quality;
%用量化步长矩阵m对变换矩阵进行量化
yy = blkproc(y, [8, 8], 'round(x./P1)', m);
y = im2col(yy, [8, 8], 'distinct'); %将图像块排列成向量
xb = size(y, 2); %得到列数，也就是子图像个数
order = [1 9 2 3 10 17 25 18 11 4 5 12 19 26 33 ... %变换系数排列次序
41 34 27 20 13 6 7 14 21 28 35 42 49 57 50 ...
43 36 29 22 15 8 16 23 30 37 44 51 58 59 52 ...
45 38 31 24 32 39 46 53 60 61 54 47 40 48 55 62 63 56 64];
%用Z形扫描方式对变换系数重新排列
y = y(order, :);
eob = max(x(:)) + 1; %创建一个块结束符号
num = numel(y) + size(y, 2);
r = zeros(num, 1);
count = 0;
%将非零元素重新排列放入r中，-26-3 eob -25 1 eob
for j = 1: xb %每次对一列（即一块）进行操作
i = max(find(y(:, j))); %找最后一个非零元素
if isempty(i) %没有非零元素
i = 0;
end
p = count + 1;
q = p + i;
r(p: q) = [y(1: i, j); eob]; %截去零并加上结束符号
count = count + i + 1;
end
r((count + 1): end) = []; %删除r的没有用的部分
r = r + 128;
%保存编码信息
y.size = uint16([xm, xn]);
y.numblocks = uint16(xb);
y.quality = uint16(quality*100);
%对r进行Huffman编码
[y.huffman, y.info] = huffencode(uint8(r));
三、运行结果
四、备注
完整代码或者代写添加QQ 1564658423
标签：index,图像去噪,vector,end,小波,len,handles,源码,codeword 来源： https://www.cnblogs.com/homeofmatlab/p/14735303.html