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《Acta Geodaetica et Cartographica Sinica》 2017-01
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An Adaptive Dense Matching Method for Airborne Images Using Texture Information

ZHU Qing;CHEN Chongtai;HU Han;DING Yulin;Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University;State-Province Joint Engineering Laboratory of Spatial Information Technology of High-speed Rail Safety,Southwest Jiaotong University;Shenzhen Research Center of Digital City Engineering;Department of Land Surveying and Geo-information;Institute of Space and Earth Information Science;  
Semi-global matching(SGM)is essentially a discrete optimization for the disparity value of each pixel,under the assumption of disparity continuities.SGM overcomes the influence of the disparity discontinuities by a set of parameters.Using smaller parameters,the continuity constraint is weakened,which will cause significant noises in planar and textureless areas,reflected as the fluctuations on the final surface reconstruction.On the other hands,larger parameters will impose too much constraints on continuities,which may lead to losses of sharp features.To address this problem,this paper proposes an adaptive dense stereo matching methods for airborne images using with texture information.Firstly,the texture is quantified,and under the assumption that disparity variation is directly proportional to the texture information,the adaptive parameters are gauged accordingly.Second,SGM is adopted to optimize the discrete disparities using the adaptively tuned parameters.Experimental evaluations using the ISPRS benchmark dataset and images obtained by the SWDC-5have revealed that the proposed method will significantly improve the visual qualities of the point clouds.
【Fund】: 国家自然科学基金(41501421;41631174;61602392);; 空间信息智能感知与服务深圳市重点实验室(深圳大学)开放基金;; 测绘遥感信息工程国家重点实验室(武汉大学)基金(15I01)~~
【CateGory Index】: TP391.41
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