1200字范文 > 【图像配准】基于matlab GUI互相关图像配准【含Matlab源码 853期】

【图像配准】基于matlab GUI互相关图像配准【含Matlab源码 853期】

时间：2020-01-22 20:04:53

一、互相关简介

在这里我想探讨一下“互相关”中的一些概念。正如卷积有线性卷积（linear convolution）和循环卷积（circular convolution）之分；互相关也有线性互相关（linear cross-correlation）和循环互相关（circular cross-correlation）。线性互相关和循环互相关的基本公式是一致的，不同之处在于如何处理边界数据。其本质的不同在于它们对原始数据的看法不同。通过这篇文章，我想整理一下相关概念，并给出示例。

1 线性相关（Linear Cross-Correlation）的定义和计算

用一个实际的应用例子来验证一下吧。如图3的第一个子图表示雷达声纳发射了一个探测信号。经过一段时间之后，收到了如图3的第二个子图所示的回波（带有一定的噪声）。此时我们关注的是如何确定回波中从何时开始是对探测信号的响应，以便计算目标距雷达的距离，这就需要用到线性互相关。在第三个子图中的‘Valid’曲线即是有效互相关数据，其中清晰地呈现出两处与探测信号相似的回波的位置。

线性互相关中，还有一些概念值得注意：

1 补零。由线性相关的计算式不难发现，为了计算出个完整的相关系数序列（包含那些“无效数据”在内的所有结果），需要用到一些“不存在”的点。这就需要人为地对这些值进行补充，在线性相关的计算中，对这些超出原始数据储存的区域取值为零。

2 末端效应。由图1可以发现，一头一尾的个互相关数据并没有完全“嵌入”两个原始数组的全部信息，它们或多或少地受到了人为补零的影响。因此一般认为这些数据是不可用的。

3 计算模式的选择。这个问题其实是由问题二衍生而来的，就Python语言中的函数而言，至少有两个可以直接计算线性相关：

2 循环互相关（Circular Cross-Correlation）的定义和计算

二、部分源代码

function varargout = xiangguan(varargin)% XIANGGUAN M-file for xiangguan.fig%XIANGGUAN, by itself, creates a new XIANGGUAN or raises the existing%singleton*.%%H = XIANGGUAN returns the handle to a new XIANGGUAN or the handle to%the existing singleton*.%%XIANGGUAN('CALLBACK',hObject,eventData,handles,...) calls the local%function named CALLBACK in XIANGGUAN.M with the given input arguments.%%XIANGGUAN('Property','Value',...) creates a new XIANGGUAN or raises the%existing singleton*. Starting from the left, property value pairs are%applied to the GUI before xiangguan_OpeningFunction gets called. An%unrecognized property name or invalid value makes property application%stop. All inputs are passed to xiangguan_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 xiangguan% Last Modified by GUIDE v2.5 20-Apr- 10:31:06% Begin initialization code - DO NOT EDITgui_Singleton = 1;gui_State = struct('gui_Name', mfilename, ...'gui_Singleton', gui_Singleton, ...'gui_OpeningFcn', @xiangguan_OpeningFcn, ...'gui_OutputFcn', @xiangguan_OutputFcn, ...'gui_LayoutFcn', [] , ...'gui_Callback', []);if nargin && ischar(varargin{1})gui_State.gui_Callback = str2func(varargin{1});endif nargout[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});elsegui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% --- Executes just before xiangguan is made visible.function xiangguan_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 xiangguan (see VARARGIN)% Choose default command line output for xiangguanhandles.output = hObject;% Update handles structureguidata(hObject, handles);% UIWAIT makes xiangguan wait for user response (see UIRESUME)% uiwait(handles.figure1);% --- Outputs from this function are returned to the command line.function varargout = xiangguan_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 structurevarargout{1} = handles.output;% --- Executes on button press in first_picture.function first_picture_Callback(hObject, eventdata, handles)% hObject handle to first_picture (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)subplot(3,3,2)[filename,pathname]=uigetfile({'*.jpg;*.tif;*.png;*.gif','All Image Files';...'*.*','All Files' },'open'); %打开路径下要检索的图像if isequal([filename,pathname],[0,0])returnelse%读取图片pic = fullfile(pathname,filename);global onion;onion = imread(pic);imshow(onion); end% --- Executes on button press in second_picture.function second_picture_Callback(hObject, eventdata, handles)% hObject handle to second_picture (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)subplot(3,3,3)[filename,pathname]=uigetfile({'*.jpg;*.tif;*.png;*.gif','All Image Files';...'*.*','All Files' },'open'); %打开路径下要检索的图像if isequal([filename,pathname],[0,0])returnelse%读取图片pict = fullfile(pathname,filename);global peppers;peppers = imread(pict);imshow(peppers); end% --- Executes on button press in correlation.function correlation_Callback(hObject, eventdata, handles)% hObject handle to correlation (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)subplot(3,3,5)global onion;global peppers;% non-interactivelyrect_onion = [111 33 65 58];rect_peppers = [163 47 143 151];sub_onion = imcrop(onion,rect_onion);sub_peppers = imcrop(peppers,rect_peppers);c = normxcorr2(sub_onion(:,:,1),sub_peppers(:,:,1));surf(c), shading flat% --- Executes on button press in overlay.function overlay_Callback(hObject, eventdata, handles)% hObject handle to overlay (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)subplot(3,3,6)global onion;global peppers;% non-interactivelyrect_onion = [111 33 65 58];rect_peppers = [163 47 143 151];sub_onion = imcrop(onion,rect_onion);sub_peppers = imcrop(peppers,rect_peppers);c = normxcorr2(sub_onion(:,:,1),sub_peppers(:,:,1));% offset found by correlation[max_c, imax] = max(abs(c(:)));[ypeak, xpeak] = ind2sub(size(c),imax(1));corr_offset = [(xpeak-size(sub_onion,2)) (ypeak-size(sub_onion,1))];% relative offset of position of subimagesrect_offset = [(rect_peppers(1)-rect_onion(1)) (rect_peppers(2)-rect_onion(2))];% total offsetoffset = corr_offset + rect_offset;xoffset = offset(1);yoffset = offset(2);xbegin = round(xoffset+1);xend = round(xoffset+ size(onion,2));ybegin = round(yoffset+1);yend = round(yoffset+size(onion,1));% extract region from peppers and compare to onionextracted_onion = peppers(ybegin:yend,xbegin:xend,:);if isequal(onion,extracted_onion) disp('onion.png was extracted from peppers.png')endrecovered_onion = uint8(zeros(size(peppers)));recovered_onion(ybegin:yend,xbegin:xend,:) = onion;imshow(recovered_onion)% --- Executes on button press in transparent.function transparent_Callback(hObject, eventdata, handles)% hObject handle to transparent (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)subplot(3,3,8)global onion;global peppers;% non-interactivelyrect_onion = [111 33 65 58];rect_peppers = [163 47 143 151];sub_onion = imcrop(onion,rect_onion);sub_peppers = imcrop(peppers,rect_peppers);c = normxcorr2(sub_onion(:,:,1),sub_peppers(:,:,1));% offset found by correlation[max_c, imax] = max(abs(c(:)));[ypeak, xpeak] = ind2sub(size(c),imax(1));corr_offset = [(xpeak-size(sub_onion,2)) (ypeak-size(sub_onion,1))];% relative offset of position of subimagesrect_offset = [(rect_peppers(1)-rect_onion(1)) (rect_peppers(2)-rect_onion(2))];