In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC) is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SAR)images effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM) are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA) optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system). The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.
DING Hao
,
ZHANG Jixian
,
HUANG Guoman
,
ZHU Jianjun
. Multi-image Matching of Airborne SAR Imagery by SANCC[J]. Acta Geodaetica et Cartographica Sinica, 2015
, 44(3)
: 274
-281
.
DOI: 10.11947/j.AGCS.2015.20140257
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