【图像融合】基于SURF算法实现红外与可见光图像配准算法附MATLAB代码

1 简介

针对SIFT(Scale Invariant Feature Transform)算法运算速度慢,提出了基于SURF(Speeded Up Robust Features)算法的图像配准.对于可见光和可见光图像,先用SURF算法提取图像的特征点,并采用64维的特征向量作为特征描述子;选用欧氏距离作为匹配方法。

2 部分代码

function ipts=OpenSurf(img,Options)% This function OPENSURF, is an implementation of SURF (Speeded Up Robust % Features). SURF will detect landmark points in an image, and describe% the points by a vector which is robust against (a little bit) rotation % ,scaling and noise. It can be used in the same way as SIFT (Scale-invariant % feature transform) which is patented. Thus to align (register) two % or more images based on corresponding points, or make 3D reconstructions.%% This Matlab implementation of Surf is a direct translation of the % OpenSurf C# code of Chris Evans, and gives exactly the same answer. % Chris Evans wrote one of the best, well structured all inclusive SURF % implementations. On his site you can find Evaluations of OpenSURF % and the C# and C++ code. http://www.chrisevansdev.com/opensurf/% Chris Evans gave me permisson to publish this code under the (Mathworks)% BSD license.%% Ipts = OpenSurf(I, Options)%% inputs,%   I : The 2D input image color or greyscale%   (optional)%   Options : A struct with options (see below)%% outputs,%   Ipts : A structure with the information about all detected Landmark points%     Ipts.x , ipts.y : The landmark position%     Ipts.scale : The scale of the detected landmark%     Ipts.laplacian : The laplacian of the landmark neighborhood%     Ipts.orientation : Orientation in radians%     Ipts.descriptor : The descriptor for corresponding point matching%% options,%   Options.verbose : If set to true then useful information is %                     displayed (default false)%   Options.upright : Boolean which determines if we want a non-rotation%                       invariant result (default false)%   Options.extended : Add extra landmark point information to the%                   descriptor (default false)%   Options.tresh : Hessian response treshold (default 0.0002)%   Options.octaves : Number of octaves to analyse(default 5)%   Options.init_sample : Initial sampling step in the image (default 2)%   % Example 1, Basic Surf Point Detection% % Load image%   I=imread('TestImages/test.png');% % Set this option to true if you want to see more information%   Options.verbose=false; % % Get the Key Points%   Ipts=OpenSurf(I,Options);% % Draw points on the image%   PaintSURF(I, Ipts);%% Example 2, Corresponding points% % See, example2.m%% Example 3, Affine registration% % See, example3.m%% Function is written by D.Kroon University of Twente (July 2010)​% Add subfunctions to Matlab Search pathfunctionname='OpenSurf.m';functiondir=which(functionname);functiondir=functiondir(1:end-length(functionname));addpath([functiondir '/SubFunctions'])       % Process inputsdefaultoptions=struct('tresh',0.0002,'octaves',5,'init_sample',2,'upright',false,'extended',false,'verbose',false);if(~exist('Options','var')),     Options=defaultoptions; else    tags = fieldnames(defaultoptions);    for i=1:length(tags)         if(~isfield(Options,tags{i})),  Options.(tags{i})=defaultoptions.(tags{i}); end    end    if(length(tags)~=length(fieldnames(Options))),         warning('register_volumes:unknownoption','unknown options found');    endend​% Create Integral Imageiimg=IntegralImage_IntegralImage(img);​% Extract the interest pointsFastHessianData.thresh = Options.tresh;FastHessianData.octaves = Options.octaves;FastHessianData.init_sample = Options.init_sample;FastHessianData.img = iimg;ipts = FastHessian_getIpoints(FastHessianData,Options.verbose);​% Describe the interest pointsif(~isempty(ipts))    ipts = SurfDescriptor_DecribeInterestPoints(ipts,Options.upright, Options.extended, iimg, Options.verbose);end​​

3 仿真结果

4 参考文献

[1]李冬梅. 基于SURF算法的红外与可见光图像配准[J]. 信息工程期刊, 2012(2).

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