Automatic Registration of Airborne and Spaceborne Images by Topology Map Matching with SURF Processor Algorithm

被引:28
作者
Brook, Anna [1 ]
Ben-Dor, Eyal [1 ]
机构
[1] Tel Aviv Univ, Dept Geog & Human Environm, Remote Sensing Lab, IL-69978 Tel Aviv, Israel
关键词
automatic registration; multi-sensor airborne and spaceborne fusion; change detection; weight-based topological map-matching algorithm (tMM); scaling and image rotation;
D O I
10.3390/rs3010065
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Image registration is widely used in remote-sensing applications. The existing automatic image registration techniques fall into two categories: Intensity-based and feature-based; the latter (which extracts structures from both images) being more suitable for multi-sensor fusion, detection of temporal changes and image mosaicking. Conventional image registration algorithms have proven to be inaccurate, time-consuming, and unfeasible due to image complexity which makes it cumbersome or even impossible to discern the appropriate control points. In this study, we propose a novel method for automatic image registration based on topology (AIRTop) for change detection and multi-sensor (airborne and spaceborne) fusion. In this algorithm, we first apply image-processing methods (SURF-Speeded-Up Robust Features) to extract the landmark structures (roads and buildings) and convert them to a features (vector) map. The following stages are applied in GIS (Geographic Information System), where topology rules, which define the permissible spatial relationships between features, are defined. The relationships between features are established by weight-based topological map-matching algorithm (tMM). The suggested algorithm presents a robust method for image registration. The main focus in this study is on scale and image rotation, when the quality of the scanning system is constant. These seem to offer a good compromise between feature complexity and robustness to commonly occurring deformations. The skew and the anisotropic scaling are assumed to be second-order effects that are covered to some degree by the overall robustness of the sensor.
引用
收藏
页码:65 / 82
页数:18
相关论文
共 28 条
[1]  
[Anonymous], INTRO MULTIVARIATE S
[2]   Speeded-Up Robust Features (SURF) [J].
Bay, Herbert ;
Ess, Andreas ;
Tuytelaars, Tinne ;
Van Gool, Luc .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2008, 110 (03) :346-359
[3]   A SURVEY OF IMAGE REGISTRATION TECHNIQUES [J].
BROWN, LG .
COMPUTING SURVEYS, 1992, 24 (04) :325-376
[4]  
BROWN M., 2002, BRIT MACHINE VISION, P656, DOI DOI 10.5244/C.16.23
[6]  
Congalton RG, 1997, PHOTOGRAMM ENG REM S, V63, P425
[7]   USE OF HOUGH TRANSFORMATION TO DETECT LINES AND CURVES IN PICTURES [J].
DUDA, RO ;
HART, PE .
COMMUNICATIONS OF THE ACM, 1972, 15 (01) :11-&
[8]  
Fan X., 2005, Proc. IEEE Conf. Applied Imagery and Pattern Recognition workshop, P80
[9]  
Florack L. M. J., 1994, Journal of Mathematical Imaging and Vision, V4, P171, DOI 10.1007/BF01249895
[10]   Automatic registration of satellite images [J].
Fonseca, LMG ;
Costa, MHM .
X BRAZILIAN SYMPOSIUM ON COMPUTER GRAPHICS AND IMAGE PROCESSING, PROCEEDINGS, 1997, :219-226