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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http://xb.chinasmp.com/EN/Y2016/V45/I7/818

References

[1] LEBERL F, DOMIK G, RRGGAM J, et al. Radar Stereo-mapping Techniques and Application to SIR-B Images of Mt. Shasta[J]. IEEE Transactions on Geoscience and Remote Sensing, 1986, GE-24(4):473-481.
[2] TOUTIN T. Evaluation of Radargrammetric DEM from RADARSAT Images in High Relief Areas[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(2):782-789.
[3] TOUTIN T. Impact of Radarsat-2 SAR Ultrafine-mode Parameters on Stereo-radargrammetric DEMs[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(10):3816-3823.
[4] CAPALDO P, CRESPI M, FRATARCANGELI F, et al. High-resolution SAR Radargrammetry:A First Application with COSMO-SkyMed SpotLight Imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(6):1100-1104.
[5] TOUTIN T, BLONDEL E, CLAVET D, et al. Stereo Radargrammetry with Radarsat-2 in the Canadian Arctic[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(5):2601-2609.
[6] DELLINGER F, DELON J, GOUSSEAU Y, et al. SAR-SIFT:A SIFT-like Algorithm for SAR Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1):453-466.
[7] 丁昊, 张继贤, 黄国满, 等. 多基线机载合成孔径雷达影像匹配的SANCC法[J]. 测绘学报, 2015, 44(3):274-281. DOI:10.11947/j.AGCS.2015.20140257. DING Hao, ZHANG Jixian, HUANG Guoman, et al. 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.
[8] BALZ T, ZHANG Lu, LIAO Mingsheng. Direct Stereo Radargrammetric Processing Using Massively Parallel Processing[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 79:137-146.
[9] GUTJAHR K, PERKO R, RAGGAM H, et al. The Epipolarity Constraint in Stereo-radargrammetric DEM Generation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8):5014-5022.
[10] RAGGAM H, GUTJAHR K, PERKO R, et al. Assessment of the Stereo-radargrammetric Mapping Potential of TerraSAR-X Multibeam Spotlight Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(2):971-977.
[11] OLLER G, ROGNANT L, MARTHON P. Correlation and Similarity Measures for SAR Image Matching[C]//Proceedings of the SPIE SAR Image Analysis, Modeling, and Techniques VI. Barcelona:SPIE, 2004, 5236:182-189.
[12] 林宗坚, 刘正坤, 支晓栋. 一种基于统计模型的自适应窗口匹配方法[J]. 测绘科学, 2010, 35(6):5-8. LIN Zongjian, LIU Zhengkun, ZHI Xiaodong. A Matching Method with Adaptive Window Based on a Statistical Model[J]. Science of Surveying and Mapping, 2010, 35(6):5-8.
[13] YOON K J, KWEON I S. Adaptive Support-weight Approach for Correspondence Search[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(4):650-656.
[14] 曹晓倩, 马彩文. 基于弱纹理检测及视差图融合的立体匹配[J]. 仪器仪表学报, 2013, 34(9):2074-2079. CAO Xiaoqian, MA Caiwen. Stereo Matching Based on Low-texture Detection and Disparity Map Fusion[J]. Chinese Journal of Scientific Instrument, 2013, 34(9):2074-2079.
[15] MERIC S, FAYARD F, POTTIER E. A Multiwindow Approach for Radargrammetric Improvements[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10):3803-3810.
[16] 贺雪艳, 张路, BALZ T, 等. 利用外部DEM辅助山区SAR立体像对匹配及地形制图[J]. 测绘学报, 2013, 42(3):425-432. HE Xueyan, ZHANG Lu, BALZ T, et al. Topographic Mapping in Mountainous Areas Using StereoSAR Assisted by External DEM[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(3):425-432.
[17] CAPALDO P, NASCETTI A, PORFIRI M, et al. Evaluation and Comparison of Different Radargrammetric Approaches for Digital Surface Models Generation from COSMO-SkyMed, TerraSAR-X, RADARSAT-2 Imagery:Analysis of Beauport (Canada) Test Site[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 100:60-70.
[18] HU Xiaoyan, MORDOHAI P. A Quantitative Evaluation of Confidence Measures for Stereo Vision[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11):2121-2133.
[19] SAYGILI G, VAN DER MAATEN L, HENDRIKS E A. Adaptive Stereo Similarity Fusion Using Confidence Measures[J]. Computer Vision and Image Understanding, 2015, 135:95-108.
[20] LEE H. Opposite-side Radargrammetry of Magellan Synthetic Aperture Radar on Venus[J]. Geosciences Journal, 2012, 16(2):165-170.
[21] EGNAL G, MINTZ M, WILDES R P. A Stereo Confidence Metric Using Single View Imagery with Comparison to Five Alternative Approaches[J]. Image and Vision Computing, 2004, 22(12):943-957.
[22] 陈尔学. 星载合成孔径雷达影像正射校正方法研究[D]. 北京:中国林业科学研究院, 2004. CHEN Erxue. Study on Ortho-rectification Methodology of Space-borne Synthetic Aperture Radar Imagery[D]. Beijing:Chinese Academy of Forestry, 2004.