IEEE Geoscience and Remote Sensing Magazine - December 2015 - 21

Xiucheng Yang, Jun Wang, Xuebin Qin,
Jianhua Wang, Xin Ye, and Qiming Qin
Institute of Remote Sensing and Geographic Information System,
School of Earth and Space Sciences, Peking University, Beijing, 100871 PR China
(e-mail: qmqinpku@163.com)

image licensed by ingram publishing

Fast Urban Aerial Image Matching Based
on Rectangular Building Extraction
Abstract-This letter presents a new approach for image matching in complex urban environments on the
basis of existing rectangular buildings. Matching veryhigh-resolution optical remote sensing imagery is important in urban-related series applications, whereas
traditional algorithms don't work well in complex urban
scenes. The proposed method conducts image matching
by combining the external contour and internal structure to construct regional features that represent a buildDigital Object Identifier 10.1109/MGRS.2015.2502280
Date of publication: 3 February 2016

ing roof, in which perceptual grouping and unsupervised classification are introduced respectively. A newly
proposed Euler number matrix combined with a conventional area index and regional histogram describes
the regional features in terms of internal heterogeneous
distribution, edge character, and spectral feature. A corresponding similarity measurement is then proposed.
Specific experiments in urban areas with repetitive patterns and poor textures prove the effectiveness and robustness of the proposed image matching approach. The
proposed technique is applied to image mosaic to confirm its feasibility for further applications.

This work was supported by the "National High-Tech Research and Development Program of China (2012AA121305)".

december 2015

ieee Geoscience and remote sensinG maGazine

0274-6638/15©2015IEEE

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