基于曲波和Markov模型的新型立体匹配算法  

Approach for Images Matching Based on Curvelet and Markov Random Field

作　　者：云挺[1,2] 肖亮[3] 吴慧中[3] 

机构地区：[1]南京林业大学信息科学技术学院,南京210037 [2]南京理工大学,计算机科学与技术学院,南京210094 [3]南京理工大学计算机科学与技术学院,南京210094

出　　处：《系统仿真学报》2009年第10期2956-2960,共5页Journal of System Simulation

基　　金：国家自然科学基金(60672074);江苏省自然科学基金(BK2006569);南京理工大学青年学者基金(Njust200401)

摘　　要：曲波变换是继小波变换后的一种新型的多尺度分析方法,它能够更好的描述图像中曲线状和超平面的奇异性问题,把曲波变换系数作为图像匹配中的基元,并结合图像分割原理和马尔可夫随机场(MRF)模型,提出了一种新的图像匹配算法,它克服了基于图像灰度的匹配方法在平滑区域或细节匮乏处无法得到正确视差的弊端,并使得视差图在物体内部平滑并保持边缘处的不连续性。实验结果表明,提出的算法无论从视觉评价上还是视差图客观指标来看,都取可得了更优的结果。Curvelet transform is a new multi-scale analysis method based on wavelet transform, and it is better suitable for describing of those images that have curve or super plane singularities. A new image matching algorithm was proposed which took curvelet transform coefficients as the image matching primitive and combined image segmentation principle with Markov random field model The approach not only overcomes these defects that image matching algorithm based on gray level can not get accurate disparity of areas where are smooth or lack of details, but also smoothes disparity inside the object boundaries and keeps the discontinuities across the boundaries. Finally, the superior visual effect and evaluation indexes of the algorithm are experimentally verified.

关 键 词：曲波变换 图像匹配 视差图 马尔可夫随机场 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]