A StereoSAR Matching Method Based on Disparity Maps Fusion

doi:10.11947/j.AGCS.2016.20160040

Abstract

Abstract: A matching algorithm based on disparity maps fusion is proposed. Firstly, on the basis of normalized cross correlation(NCC), various disparity maps are computed using several different matching window sizes. Then, for each disparity of each disparity maps, the confidence level is evaluated by a new confidence measure, which combined left right consistency(LRC) with signal to noise ratio(SNR). Finally, a new proposed disparity maps fusion strategy is used for formation of weighted disparity map in terms of confidence level. This disparity maps fusion strategy considers not only the confidence level of the disparity itself but also its neighbors. The algorithm has been applied to a pair of TanDEM-X spotlight stereo images. The results demonstrate that the accuracy of DEM generated with the proposed algorithm is improved from 11.28 m to 8.41 m and the gross errors are effectively reduced.

Key words: normalized cross correlation(NCC), disparity maps fusion, confidence measure, radargrammetry

CLC Number:

P237

WANG Yachao, ZHANG Jixian, HUANG Guoman, LU Lijun, DING Hao. A StereoSAR Matching Method Based on Disparity Maps Fusion[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(7): 818-824.

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