结合多尺度特征与局部采样描述的多模态图像配准方法

打开文本图片集

Research on multimodal image registration method combining multi-scale features and local sampling description

Jia Zhiyou，Wang Guogang （School of Information Enginering，Shenyang Chemical University，Shenyang11O142，China）

Abstract：Aimingatthematching dificultiescausedbytheexistenceofserious geometricdiferencesandnonlinearntensity diference（NID）indiferentmodal images，this paperproposedamultimodal imagealignmentmethodcombining multi-scale featureswithalocalsamplingdescription.Firstly，themethodintroducedanonlineardifusionequationtoconstructanonlinearscalespace，andthen itcombineda phaseconsistencyandorientedFASTandrotatedBRIEF（ORB）algorithm to obtain multi-scalestable feature points.Then，the method proposedarotation-invariant doubleGaussiansamplingdescriptor，which could robustly span the rotation difference of [0∘，360∘） in the presence of NID. Finally，the method introduced an image recoverystrategy.The methodobtainedtheoptimal geometrictransformationmodel through primarymatching，corected the geometricdiferences existingbetween images，andthenperformed secondarymatching toimprovethematchingaccuracy. Experiments on multimodal data sets inremote sensing，medicine，andcomputer visionshowthattheroot-mean-squareerorof the proposed method can reach within 1.5 pixels and the correct matching rate can exceed 98% when there are geometric diferencessuchasscaleandrotation.Theresultsdemonstrate that this methodcanovercometheinfluenceof nonlinearradiation difference between images and achieve high precision registration.

Keywords：multimodalimages registration；nonlinear scale space；phase coherence；double Gausian sampling descriptor; nonlinear radial disparity

0 引言

图像匹配是计算机视觉领域的一个基础和关键问题，其目的是在两幅或多幅图像中提取可靠的特征对应，使之成为图像融合、图像检测、目标跟踪等多个领域的先决条件。（剩余14258字）