基于抽象匹配流的彩色图像配准模型  

Color Image Registration Model Based on Abstract Matching Flow

作　　者：白小晶[1] 陈允杰[2] 张洁玉[1] 孙怀江[1] 王平安[3] 夏德深[1] 

机构地区：[1]南京理工大学计算机科学与技术学院,南京210094 [2]南京信息工程大学数学系,南京210044 [3]香港中文大学计算机科学与工程学系,中国香港

出　　处：《计算机辅助设计与图形学学报》2009年第2期229-236,共8页Journal of Computer-Aided Design & Computer Graphics

基　　金：香港特区政府研究资助局研究项目(CUHK/4185/00E);香港中文大学研究基金(2050345)

摘　　要：在抽象匹配流框架下,构造能够克服大色差问题的彩色图像配准模型.该模型中,数据项采用互相关函数作为2幅图像间的相似性度量,以解决大色差问题;正则项采用各向异性扩散滤波器约束图像演化,从而实现在演化过程中对图像特征的有效保持.扩散滤波器中的扩散系数定义为关于彩色结构张量的函数,以使图像演化能够综合各通道信息,解决了各通道所得位移场不一致而引起的色彩混迭问题.实验结果表明,文中模型对具有大色差的彩色图像能够实现有效配准.A color image registration model within the framework of abstract matching flow is proposed to deal with the problem of serious color difference between registered images. The model is composed of a data term and a regularization term. The data term employs the cross correlation as the similarity measurement between two images, in order to cope with the large color difference problem. The regularization term into which an anisotropic flow-driven diffusion is introduced, aims at preserving image features during the image evolution. The diffusion structure tensor in the diffusion coefficient function is a vector-valued structure tensor, which integrates the intensity and structure information of each channel, as well as the correlation among channels. Experimental results validate the proposed model, especially for images of large color difference.

关 键 词：彩色图像配准 抽象匹配流 互相关函数 各向异性扩散 彩色结构张量 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]