基于阴影概率约束的遥感影像建筑物阴影检测
|
摘要
针对高分辨率遥感影像中建筑物阴影检测的需求,通过主成分变换和色调、色饱和度和强度(HSI)空间中阴影的光谱特性提取,开展了基于阴影概率约束的阴影检测方法研究。根据主成分变换结果与地物在HSI空间光谱特性的差异,消除暗色地物的影响,并用阴影概率检测存在于水体中的建筑物阴影,避免了传统方法由于水体与建筑物阴影光谱特征相近而引起的误检和漏检现象。基于吉林一号卫星影像的实验结果证明,所提方法的误检率和漏检率低于6%,总体分类精度和Kappa系数高于0.9,水体对阴影检测结果的影响明显降低,影像中阴影的整体检测效果得到提升。
In order to meet the needs of building shadow detection in high resolution remote sensing images,we study the shadow detection method based on shadow probability constraint by principal component transformation and spectral feature extraction in hue,saturation,and intensity(HSI)space.Based on the results of principal component transformation and the difference of the spectral characteristics of ground objects in HSI space,we eliminate the influence of dark objects and detect the shadow of buildings in the water using shadow probability.Compared with traditional methods,the proposed method avoids the false detection and missed detection caused by the similar spectral characteristics of water bodies and buildings.Experimental results based on Jilin No.1 images show that the false detection rate and missed detection rate of the proposed method are less than 6%,the overall classification accuracy and Kappa coefficient are higher than 0.9,the impact of water on shadow detection results is reduced,and the overall effect of image shadow detection is improved.
In order to meet the needs of building shadow detection in high resolution remote sensing images,we study the shadow detection method based on shadow probability constraint by principal component transformation and spectral feature extraction in hue,saturation,and intensity(HSI)space.Based on the results of principal component transformation and the difference of the spectral characteristics of ground objects in HSI space,we eliminate the influence of dark objects and detect the shadow of buildings in the water using shadow probability.Compared with traditional methods,the proposed method avoids the false detection and missed detection caused by the similar spectral characteristics of water bodies and buildings.Experimental results based on Jilin No.1 images show that the false detection rate and missed detection rate of the proposed method are less than 6%,the overall classification accuracy and Kappa coefficient are higher than 0.9,the impact of water on shadow detection results is reduced,and the overall effect of image shadow detection is improved.
引文
[1]Wang J,Qin Q M,Ye X,et al.A survey of building extraction methods from optical high resolution remote sensing imagery[J].Remote Sensing Technology and Application,2016,31(4):653-662.王俊,秦其明,叶昕,等.高分辨率光学遥感图像建筑物提取研究进展[J].遥感技术与应用,2016,31(4):653-662.
[2]Chen H S,He H,Xiao H Y,et al.Shadow detection in high spatial resolution remote sensing images based on spectral features[J].Optics and Precision Engineering,2015,23(10):484-490.陈红顺,贺辉,肖红玉,等.基于光谱特征的高空间分辨率遥感影像阴影检测[J].光学精密工程,2015,23(10):484-490.
[3]Makarau A,Richter R,Muller R,et al.Adaptive shadow detection using a blackbody radiator model[J].IEEE Transactions on Geoscience and Remote Sensing,2011,49(6):2049-2059.
[4]Tsai V J D.A comparative study on shadow compensation of color aerial images in invariant color models[J].IEEE Transactions on Geoscience and Remote Sensing.2006,44(6):1661-1671.
[5]Yang J,Zhao Z M,Yang J.A shadow removal method for high resolution remote sensing image[J].Geomatics and Information Science of Wuhan University,2008,33(1):17-20.杨俊,赵忠明,杨健.一种高分辨率遥感影像阴影去除方法[J].武汉大学学报信息科学版,2008,33(1):17-20.
[6]Yao H Q,Yang S W,Liu Z J,et al.A method of shadow detection for city tall ground objects based on QuickBird images[J].Remote Sensing for Land and Resources,2015,27(2):51-55.姚花琴,杨树文,刘正军,等.基于QuickBird影像的城市高大地物阴影检测方法[J].国土资源遥感,2015,27(2):51-55.
[7]Murali S,Govindan V K.Shadow detection and removal from a single image using LAB color space[J].Cybernetics&Information Technologies,2013,13(1):95-103.
[8]Liu H,Xie T W.Study on shadow detection in high resolution remote sensing image based on PCA and HSI model[J].Remote Sensing Technology and Application,2013,28(1):78-84.刘辉,谢天文.基于PCA与HSI模型的高分辨率遥感影像阴影检测研究[J].遥感技术与应用,2013,28(1):78-84.
[9]Jung C R.Efficient background subtraction and shadow removal for monochromatic video sequences[J].IEEE Transactions on Multimedia,2009,11(3):571-577.
[10]Leone A,Distante C.Shadow detection for moving objects based on texture analysis[J].Pattern Recognition,2007,40(4):1222-1233.
[11]Xu J,Xiang W B,Mao Y B,et al.Moving object shadow detection based on regional color clustering[J].Computer Technology and Development,2016,26(3):193-196.徐杰,项文波,茅耀斌,等.基于区域颜色聚类的运动目标阴影检测[J].计算机技术与发展,2016,26(3):193-196.
[12]Ai W L,Wu Z H,Liu Y L.Outdoor shadow detection with paired regions[J].Journal of Image and Graphics,2015,20(4):551-558.艾维丽,吴志红,刘艳丽.结合区域配对的室外阴影检测[J].中国图象图形学报,2015,20(4):551-558.
[13]Zhou X L,Guo J W,Liu K M.Water body information extraction based on operational land imager imagery and principal component analysis:Acase study of Poyang Lake region[J].Laser&Optoelectronics Progress,2016,53(8):080104.周小莉,郭加伟,刘琨铭.基于陆地成像仪影像和主成分分析的水体信息提取---以鄱阳湖区为例[J].激光与光电子学进展,2016,53(8):080104.
[14]Shuai T,Zhang H Y,Zhang L P.The objected-based method of shadow detection in high-resolution remote sensing imagery[J].Acta Photonica Sinica,2015,44(12):1228002.帅滔,张洪艳,张良培.面向对象的高分辨遥感影像阴影探测方法[J].光子学报,2015,44(12):1228002.
[15]Li D W,Yang F B,Wang X X.Multisource remote sensing classification based on random forest and adaptive weighted D-S evidence synthesis[J].Laser&Optoelectronics Progress,2016,53(3):031001.李大威,杨风暴,王肖霞.基于随机森林与D-S证据合成的多源遥感分类研究[J].激光与光电子学进展,2016,53(3):031001.
[16]Deng L,Deng M J,Zhang L S.Optimization of shadow detection and compensation method for highresolution remote sensing images[J].Remote Sensing Technology and Application,2015,30(2):277-284.邓琳,邓明镜,张力树.高分辨率遥感影像阴影检测与补偿方法优化[J].遥感技术与应用,2015,30(2):277-284.
[17]Su Y Z,Li A H,Jin G Z,el al.Multi-feature HSItogram back-projection for moving shadow detection[J].Journal of Optoelectronics·Laser,2014,25(7):1395-1402.苏延召,李艾华,金广智,等.结合直方图反投影的多特征运动阴影检测算法[J].光电子·激光.2014,25(7):1395-1402.
[18]Xu Y,Wei Z Y.An improved traffic sign image recognition algorithm[J].Laser&Optoelectronics Progress.2017,54(2):021001.徐岩,韦镇余.一种改进的交通标志图像识别算法[J].激光与光电子学进展,2017,54(2):021001.
[19]Duan Z G,Qu L Q,Tian J D,et al.Outdoor illumination shadow detection based on orthogonal decomposition[J].Acta Optica Sinica,2016,36(8):0815002.段志刚,屈靓琼,田建东,等.基于正交分解的室外光照阴影检测[J].光学学报,2016,36(8):0815002.
[20]Levin A,Lischinski D,Weiss Y.A closed-form solution to natural image matting[J].IEEETransactions on Pattern Analysis and Machine Intelligence,2008,30(2):228-242.
[21]Su N,Zhang Y,Tian S,et al.Shadow detection and removal for occluded object information recovery in urban high-resolution panchromatic satellite images[J].IEEE Journal of Selected Topics in Applied Earth Observations&Remote Sensing,2016,9(6):2568-2582.
[22]Liu D W,Han L,Han X Y.High spatial resolution remote sensing image classification based on deep learning[J].Acta Optica Sinica,2016,36(4):0428001.刘大伟,韩玲,韩晓勇.基于深度学习的高分辨率遥感影像分类研究[J].光学学报,2016,36(4):0428001.
[23]Li P W,Ge W Y,Liu G Y.Shadow detection method based on shadow probability model for remote sensing images[J].Journal of Computer Applications,2015,35(2):510-514.李鹏伟,葛文英,刘国英.基于阴影概率模型的遥感影像阴影检测方法[J].计算机应用,2015,35(2):510-514.
[2]Chen H S,He H,Xiao H Y,et al.Shadow detection in high spatial resolution remote sensing images based on spectral features[J].Optics and Precision Engineering,2015,23(10):484-490.陈红顺,贺辉,肖红玉,等.基于光谱特征的高空间分辨率遥感影像阴影检测[J].光学精密工程,2015,23(10):484-490.
[3]Makarau A,Richter R,Muller R,et al.Adaptive shadow detection using a blackbody radiator model[J].IEEE Transactions on Geoscience and Remote Sensing,2011,49(6):2049-2059.
[4]Tsai V J D.A comparative study on shadow compensation of color aerial images in invariant color models[J].IEEE Transactions on Geoscience and Remote Sensing.2006,44(6):1661-1671.
[5]Yang J,Zhao Z M,Yang J.A shadow removal method for high resolution remote sensing image[J].Geomatics and Information Science of Wuhan University,2008,33(1):17-20.杨俊,赵忠明,杨健.一种高分辨率遥感影像阴影去除方法[J].武汉大学学报信息科学版,2008,33(1):17-20.
[6]Yao H Q,Yang S W,Liu Z J,et al.A method of shadow detection for city tall ground objects based on QuickBird images[J].Remote Sensing for Land and Resources,2015,27(2):51-55.姚花琴,杨树文,刘正军,等.基于QuickBird影像的城市高大地物阴影检测方法[J].国土资源遥感,2015,27(2):51-55.
[7]Murali S,Govindan V K.Shadow detection and removal from a single image using LAB color space[J].Cybernetics&Information Technologies,2013,13(1):95-103.
[8]Liu H,Xie T W.Study on shadow detection in high resolution remote sensing image based on PCA and HSI model[J].Remote Sensing Technology and Application,2013,28(1):78-84.刘辉,谢天文.基于PCA与HSI模型的高分辨率遥感影像阴影检测研究[J].遥感技术与应用,2013,28(1):78-84.
[9]Jung C R.Efficient background subtraction and shadow removal for monochromatic video sequences[J].IEEE Transactions on Multimedia,2009,11(3):571-577.
[10]Leone A,Distante C.Shadow detection for moving objects based on texture analysis[J].Pattern Recognition,2007,40(4):1222-1233.
[11]Xu J,Xiang W B,Mao Y B,et al.Moving object shadow detection based on regional color clustering[J].Computer Technology and Development,2016,26(3):193-196.徐杰,项文波,茅耀斌,等.基于区域颜色聚类的运动目标阴影检测[J].计算机技术与发展,2016,26(3):193-196.
[12]Ai W L,Wu Z H,Liu Y L.Outdoor shadow detection with paired regions[J].Journal of Image and Graphics,2015,20(4):551-558.艾维丽,吴志红,刘艳丽.结合区域配对的室外阴影检测[J].中国图象图形学报,2015,20(4):551-558.
[13]Zhou X L,Guo J W,Liu K M.Water body information extraction based on operational land imager imagery and principal component analysis:Acase study of Poyang Lake region[J].Laser&Optoelectronics Progress,2016,53(8):080104.周小莉,郭加伟,刘琨铭.基于陆地成像仪影像和主成分分析的水体信息提取---以鄱阳湖区为例[J].激光与光电子学进展,2016,53(8):080104.
[14]Shuai T,Zhang H Y,Zhang L P.The objected-based method of shadow detection in high-resolution remote sensing imagery[J].Acta Photonica Sinica,2015,44(12):1228002.帅滔,张洪艳,张良培.面向对象的高分辨遥感影像阴影探测方法[J].光子学报,2015,44(12):1228002.
[15]Li D W,Yang F B,Wang X X.Multisource remote sensing classification based on random forest and adaptive weighted D-S evidence synthesis[J].Laser&Optoelectronics Progress,2016,53(3):031001.李大威,杨风暴,王肖霞.基于随机森林与D-S证据合成的多源遥感分类研究[J].激光与光电子学进展,2016,53(3):031001.
[16]Deng L,Deng M J,Zhang L S.Optimization of shadow detection and compensation method for highresolution remote sensing images[J].Remote Sensing Technology and Application,2015,30(2):277-284.邓琳,邓明镜,张力树.高分辨率遥感影像阴影检测与补偿方法优化[J].遥感技术与应用,2015,30(2):277-284.
[17]Su Y Z,Li A H,Jin G Z,el al.Multi-feature HSItogram back-projection for moving shadow detection[J].Journal of Optoelectronics·Laser,2014,25(7):1395-1402.苏延召,李艾华,金广智,等.结合直方图反投影的多特征运动阴影检测算法[J].光电子·激光.2014,25(7):1395-1402.
[18]Xu Y,Wei Z Y.An improved traffic sign image recognition algorithm[J].Laser&Optoelectronics Progress.2017,54(2):021001.徐岩,韦镇余.一种改进的交通标志图像识别算法[J].激光与光电子学进展,2017,54(2):021001.
[19]Duan Z G,Qu L Q,Tian J D,et al.Outdoor illumination shadow detection based on orthogonal decomposition[J].Acta Optica Sinica,2016,36(8):0815002.段志刚,屈靓琼,田建东,等.基于正交分解的室外光照阴影检测[J].光学学报,2016,36(8):0815002.
[20]Levin A,Lischinski D,Weiss Y.A closed-form solution to natural image matting[J].IEEETransactions on Pattern Analysis and Machine Intelligence,2008,30(2):228-242.
[21]Su N,Zhang Y,Tian S,et al.Shadow detection and removal for occluded object information recovery in urban high-resolution panchromatic satellite images[J].IEEE Journal of Selected Topics in Applied Earth Observations&Remote Sensing,2016,9(6):2568-2582.
[22]Liu D W,Han L,Han X Y.High spatial resolution remote sensing image classification based on deep learning[J].Acta Optica Sinica,2016,36(4):0428001.刘大伟,韩玲,韩晓勇.基于深度学习的高分辨率遥感影像分类研究[J].光学学报,2016,36(4):0428001.
[23]Li P W,Ge W Y,Liu G Y.Shadow detection method based on shadow probability model for remote sensing images[J].Journal of Computer Applications,2015,35(2):510-514.李鹏伟,葛文英,刘国英.基于阴影概率模型的遥感影像阴影检测方法[J].计算机应用,2015,35(2):510-514.