计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 57-60.doi: 10.11896/j.issn.1002-137X.2015.06.013
岳昕,尚振宏,强振平,刘 辉,付晓东,张志华
YUE Xin, SHANG Zhen-hong, QIANG Zhen-ping, LIU Hui, FU Xiao-dong and ZHANG Zhi-hua
摘要: 天文图像配准是研究天体运动的一项关键技术,图像内部结构往往存在轻微的不规则运动。但是图像配准涉及到计算整个图像的变换关系,在此情况下,无论是采用基于统计特征还是基于局部特征的配准方法,都难以取得理想的效果。为此,提出基于信息熵与SIFT算法的天文图像配准方法。该方法首先需对图像进行均匀分块并计算每块熵值,以熵值最大者作为配准的局部子图,然后通过尺度不变特征变换(Scale Invariant Feature Transform,SIFT)及仿射变换建立变换关系,继而利用局部子图变换关系完成图像的配准。该方法一方面能缩短变换关系的建立时间,另一方面能保证图像中信息熵最大区域配准,有效提高天文图像配准质量。
[1] Zitova B,Flusser J.Image registration methods:a survey[J].Image and vision computing,2003,21(11):977-1000 [2] Lowe D G.Object recognition from local scale-invariant features[C]∥The proceedings of the seventh IEEE international conference on Computer Vision,1999.IEEE,1999,2:1150-1157 [3] Lowe D G.Distinctive image features from scale-invariant keypoints[J].International journal of computer vision,2004,60(2):91-110 [4] 王永明,王贵锦.图像局部不变性特征与描述[M].北京:国防工业出版社,2010 Wang Yong-ming,Wang Gui-jin.Image Local Invariant Features and Description[M].Beijing:National Defense Industry Press,2010 [5] Mikolajczyk K,Schmid C.A performance evaluation of local descriptors[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(10):1615-1630 [6] 周锋飞,陈卫东,李良福.一种基于区域生长的红外Z与可见光的图像融合方法[J].应用光学,2007,28(6):737-741 Zhou Feng-fei,Chen Wei-dong,Li Liang-fu.Fusion of IR and Visible Image Using Region Growing[J].Journal of Applied Opties,2007,28(6):737-741 [7] Zheng J,Tian J,Deng K,et al.Salient feature region:a new method for retinal image registration[J].IEEE Transactions on Information Technology in Biomedicine,2011,15(2):221-232 [8] 孟芳兵.一种基于最大区域熵值的图像融合方法[J].武汉理工大学学报:信息与管理工程版,2009,31(1):19-21 Meng Fang-bing.An Image Fusion Technique Based on the Maximum Region Entropy[J].Journal of WVT:Information & Management Engineering,2009,1(1):19-21 [9] Koenderink J J.The structure of images[J].Biological cyberneti-cs,1984,50(5):363-370 [10] Florack L M J,ter Haar Romeny B M,Koenderink J J,et al.Scale and the differential structure of images[J].Image and Vision Computing,1992,10(6):376-388 [11] Lindeberg T.Scale-space theory in computer vision[M].Sprin-ger,1993 |
No related articles found! |
|