Automatic image registration based on convexity model and full-scale image segmentation

被引:1
|
作者
Sun, Kaimin [1 ]
Sui, Haigang [2 ]
Chen, Yan [1 ]
机构
[1] Wuhan Univ, Sch Remote Sensing Informat Engn, 129 Luoyu Rd, Wuhan 430079, Peoples R China
[2] Wuhan Univ, Natl Lab Informat Engn Surveying Mapping & Remote, Wuhan 430079, Peoples R China
关键词
convexity model; full-scale image segmentation; image registration; criterion of similarity; change detection;
D O I
10.1117/12.751051
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Image registration plays a critically important role in many practical problems in diverse fields. A new object-oriented image matching algorithm is presented based on the convexity model (CM) and full-scale image segmentation. The core idea of this matching algorithm is to use image objects as matching unit rather than points or lines. This algorithm firstly converts images into image objects trees by full-scale segmentation and convexity model restriction. Because image objects which accord with the convexity model have rich and reliable statistical information and stable shapes, more characteristics can be used in object-based image matching than pixel-based image matching. Initial experiments show that matching algorithm proposed in this paper is not sensitive to rotation and resolution distortion, which can accomplish the image matching and registration automatically.
引用
收藏
页数:9
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