基于SURF的月球影像ROI检测  

ROI detection method for lunar imagery based on SURF

作　　者：陈慧中[1,2] 陈永光[3] 景宁[1] 陈荦[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073 [2]西南电子电信技术研究所上海分所,上海200434 [3]军械工程学院,河北石家庄050003

出　　处：《红外与毫米波学报》2011年第6期561-565,570,共6页Journal of Infrared and Millimeter Waves

基　　金：国家"863"高技术研究发展计划项目(2008AA12A211;2009AA7010413)

摘　　要：根据月球影像的光照特点,分析了月球影像的感兴趣区域(ROI)特点与局部视觉特征的关系,构建了基于快速鲁棒性特征(SURF)的月球影像撞击坑模型.在此基础上提出了月球影像ROI检测算法:提取月球影像中撞击坑明亮面与阴影面的SURF点,合并相互交叠的同质区域,依据月球影像撞击坑模型的构建约束进行明暗特征对组合,形成ROI.针对嫦娥一号及嫦娥二号月球影像数据进行ROI检测,实验结果表明基于SURF的月球影像ROI检测方法能准确地提取影像中显著的撞击坑区域,检测效果明显好于经典的Itti检测方法.A Lunar Impact Crater Model is proposed by analyzing the relationship between region of interest（ROI） and local salient features of lunar imagery according to the illumination characteristics.Based on the model,an ROI detection algorithm is proposed.SURF of the highlight region and shadow region of an impact crater are extracted at first;then the homogeneous features are merged into new ones.According to the constructive constrains of the Lunar Impact Crater Model,pairs of highlight feature and shadow feature are combined to generate the ROI.The algorithm has been put into test on Chang＇e-1 and Chang＇e-2 lunar imagery data,and was able to correctly detect the obvious regions of impact craters with results much better than those obtained by Itti algorithm.

关 键 词：月球影像 显著区域检测 快速鲁棒性特征 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]