高分辨率光学遥感几何与纹理约束的线段优化算法
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摘要
针对高分辨率光学遥感影像线段断裂问题,提出一种基于几何与纹理约束的线段优化算法。首先,将线段视为地物轮廓表达的一种方式,由此从同一地物边缘角度出发,提出线段断裂的几何与纹理规律;其次,提出线段优化算法,以提取线段结果为处理基元,依据线段长度确定初始优化线段,设定跟踪矩形,建立针对断裂线段的几何纹理约束模型,构建动态优化模型,并给出完整的线段优化流程。最后,通过多幅不同实际场景、不同类型高分辨率遥感影像的试验结果分析,表明本文算法不仅能够解决由地物遮挡、边缘模糊及边缘锯齿化造成的线段断裂问题,并且在优化线段长度以及抑制线段过提取问题方面,均表现出较大的优势。
Aiming at the problem that high-resolution optical remote sensing image lines are prone to fracture, a line segment optimization algorithm is proposed. Firstly, the line segment is regarded as a way to express the contour of the ground object, and the laws of line segment fracture from two aspects of geometric features and texture features are analyzed. Secondly, the line segment optimization algorithm is proposed. It takes the results of detecting line segments as the processing primitives, determines the initial optimized line segment according to the length of the line segment, establishes the tracking rectangular region and geometric constraint model for the broken line segments,build a dynamic optimization model, and give a complete line optimization process. Through the analysis of experimental results of some actual scenes and different types of remote sensing images, it is shown that the proposed algorithm can not only solve the problem of line segment fracture caused by terrain occlusion, edge blurring and edge serration, but also comparing with other methods, the proposed algorithm has great advantages in optimizing line length and restraining over extraction problem.
Aiming at the problem that high-resolution optical remote sensing image lines are prone to fracture, a line segment optimization algorithm is proposed. Firstly, the line segment is regarded as a way to express the contour of the ground object, and the laws of line segment fracture from two aspects of geometric features and texture features are analyzed. Secondly, the line segment optimization algorithm is proposed. It takes the results of detecting line segments as the processing primitives, determines the initial optimized line segment according to the length of the line segment, establishes the tracking rectangular region and geometric constraint model for the broken line segments,build a dynamic optimization model, and give a complete line optimization process. Through the analysis of experimental results of some actual scenes and different types of remote sensing images, it is shown that the proposed algorithm can not only solve the problem of line segment fracture caused by terrain occlusion, edge blurring and edge serration, but also comparing with other methods, the proposed algorithm has great advantages in optimizing line length and restraining over extraction problem.
引文
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[21]李畅,李芳芳.基于假设检验的数字影像线状特征亚像素自动提取[J].测绘学报,2013,42(1):67-72.LI Chang,LI Fangfang.Auto-extracting sub-pixel line feature of digital images based on hypothesis testing[J].Acta Geodaetica et Cartographica Sinica,2013,42(1):67-72.
[22]CHO N G,YUILLE A,LEE S W.A novel linelet-based representation for line segment detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2018,40(5):1195-1208.
[23]朱昌盛,周伟,关键.基于平行线对检测的SAR图像主干道提取算法[J].中国图象图形学报,2011,16(10):1908-1917.ZHU Changsheng,ZHOU Wei,GUAN Jian.Main road extraction from SAR imagery based on parallel pairs detection[J].Journal of Image and Graphics,2011,16(10):1908-1917.
[24]STEGER C,ULRICH M,WIEDEMANN C.机器视觉算法与应用[M].杨少荣,吴迪靖,段德山,译.北京:清华大学出版社,2008.STEGER C,ULRICH M,WIEDEMANN C.Machine vision algorithms and applications[M].YANG Shaorong,WUDijing,DUAN Deshan,trans.Beijing:Tsinghua University Press,2008.
[25]SARKAR S.An introduction to perceptual organization[C]∥Proceedings of the IEMC’03 Proceedings.Managing Technologically Driven Organizations:The Human Side of Innovation and Change.Cambridge,MA:IEEE,2003:330-335.
[2]MARSHALL S.Line structure representation for road network analysis[J].The Journal of Transport and Land Use,2016,9(1):29-64.
[3]WANG C K,HSU P H.Building detection and structure line extraction from airborne LiDAR data[J].Journal of Photogrammetry and Remote Sensing,2007,12(4):365-379.
[4]TSENG Y H,HUNG H C.Extraction of building boundary lines from airborne LiDAR point clouds[J].ISPRS-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2016,XLI-B3:957-962.
[5]戴激光,张力,李晋威,等.2017.一种链码跟踪与相位验证相结合的直线提取方法[J].测绘学报,2017,46(2):218-227.DOI:10.11947/j.AGCS.2017.20160303.DAI Jiguang,ZHANG Li,LI Jinwei,et al.A line extraction method for chain code tracking with phase verification[J].Acta Geodaetica et Cartographica Sinica,2017,46(2):218-227.DOI:10.11947/j.AGCS.2017.20160303.
[6]BALLARD D H.Generalizing the Hough transform to detect arbitrary shapes[J].Pattern Recognition,1981,13(2):111-122.
[7]徐胜华,朱庆,刘纪平,等.基于预存储权值矩阵的多尺度Hough变换直线提取算法[J].测绘学报,2008,37(1):83-88.DOI:10.3321/j.issn:1001-1595.2008.01.015.XU Shenghua,ZHU Qing,LIU Jiping,et al.Straight line extraction via multi-scale Hough transform based on prestorage weight matrix[J].Acta Geodaetica et Cartographica Sinica,2008,37(1):83-88.DOI:10.3321/j.issn:1001-1595.2008.01.015.
[8]王竞雪,朱庆,王伟玺,等.结合边缘编组的Hough变换直线提取[J].遥感学报,2014,18(2):378-389.WANG Jingxue,ZHU Qing,WANG Weixi,et al.Straight line extraction algorithm by Hough transform combining edge grouping[J].Journal of Remote Sensing,2014,18(2):378-389.
[9]XU Zezhong,SHIN B S,KLETTE R.Accurate and robust line segment extraction using minimum entropy with Hough transform[J].IEEE Transactions on Image Processing,2015,24(3):813-822.
[10]BURNS J B,HANSON A R,RISEMAN E M.Extracting straight lines[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,PAMI-8(4):425-455.
[11]FREEMAN H.Boundary encoding and processing[M]∥LIPKIN B S,ROSENFELD A.Picture Processing and Psychopictorics.New York:Academic Press,1970:241-266.
[12]赵丽科,宋伟东,王竞雪.Freeman链码优先级直线提取算法研究[J].武汉大学学报(信息科学版),2014,39(1):42-46.ZHAO Like,SONG Weidong,WANG Jingxue.Straight line extraction algorithm of freeman chain code priority[J].Geomatics and Information Science of Wuhan University,2014,39(1):42-46.
[13]王竞雪,朱庆,张云生,等.叠置分区辅助的相位编组直线提取算法[J].测绘学报,2015,44(7):768-774,790.WANG Jingxue,ZHU Qing,ZHANG Yunsheng,et al.Phase grouping line extraction algorithm using overlapped partition[J].Acta Geodaetica et Cartographica Sinica,2015,44(7):768-774,790.
[14]李畅,魏东.一个基于像素编组和逐级质量控制的线段检测算子[J].红外与毫米波学报,2016,35(6):681-687.LI Chang,WEI Dong.A line segment detector based on pixels grouping and step-by-step quality control[J].Journal of Infrared and Millimeter Waves,2016,35(6):681-687.
[15]VON GIOI R G,JAKUBOWICZ J,MOREL J M,et al.LSD:A fast line segment detector with a false detection control[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(4):722-732.
[16]AKINLAR C,TOPAL C.EDLines:a real-time line segment detector with a false detection control[J].Pattern Recognition Letters,2011,32(13):1633-1642.
[17]刘博,徐丽华,卢盛昌.关于建筑物图像提取优化仿真研究[J].计算机仿真,2015,32(12):327-331.LIU Bo,XU Lihua,LU Shengchang.Simulation of extraction and optimization for building image[J].Computer Simulation,2015,32(12):327-331.
[18]席学强,翟为刚,卢利斌.基于感知组织的直线段编组方法[J].计算机应用研究,2002,19(6):64-67.XI Xueqiang,ZHAI Weigang,LU Libin.The approach of grouping straight line segments based on perceptual organization[J].Application Research of Computer,2002,19(6):64-67.
[19]戴激光,张力,朱恩泽,等.遥感影像主特征线检测[J].遥感学报,2017,21(2):228-238.DAI Jiguang,ZHANG Li,ZHU Enze,et al.Principal line detection in remote sensing image[J].Journal of Remote Sensing,2017,21(2):228-238.
[20]陈仁杰,刘利刚,董光昌.图像主特征直线的检测算法[J].中国图象图形学报,2010,15(3):403-408.CHEN Renjie,LIU Ligang,DONG Guangchang.Detection of principal lines in images[J].Journal of Image and Graphics,2010,15(3):403-408.
[21]李畅,李芳芳.基于假设检验的数字影像线状特征亚像素自动提取[J].测绘学报,2013,42(1):67-72.LI Chang,LI Fangfang.Auto-extracting sub-pixel line feature of digital images based on hypothesis testing[J].Acta Geodaetica et Cartographica Sinica,2013,42(1):67-72.
[22]CHO N G,YUILLE A,LEE S W.A novel linelet-based representation for line segment detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2018,40(5):1195-1208.
[23]朱昌盛,周伟,关键.基于平行线对检测的SAR图像主干道提取算法[J].中国图象图形学报,2011,16(10):1908-1917.ZHU Changsheng,ZHOU Wei,GUAN Jian.Main road extraction from SAR imagery based on parallel pairs detection[J].Journal of Image and Graphics,2011,16(10):1908-1917.
[24]STEGER C,ULRICH M,WIEDEMANN C.机器视觉算法与应用[M].杨少荣,吴迪靖,段德山,译.北京:清华大学出版社,2008.STEGER C,ULRICH M,WIEDEMANN C.Machine vision algorithms and applications[M].YANG Shaorong,WUDijing,DUAN Deshan,trans.Beijing:Tsinghua University Press,2008.
[25]SARKAR S.An introduction to perceptual organization[C]∥Proceedings of the IEMC’03 Proceedings.Managing Technologically Driven Organizations:The Human Side of Innovation and Change.Cambridge,MA:IEEE,2003:330-335.