An automatic shadow detection method for high-resolution remote sensing imagery based on polynomial fitting
An automatic shadow detection method for high-resolution remote sensing imagery based on polynomial fitting
复制标题
基于多项式拟合的高分辨率遥感影像自动阴影检测方法
DOI：
10.1080/01431161.2018.1538586
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发表时间：
2018-11
影响因子：
3.4
通讯作者：
Ma Jijing
中科院分区：
文献类型：
--
作者：
Xue Li;Yang Shuwen;Li Yikun;Ma Jijing
大多数现有的阴影检测模型和算法需要大量的计算，并且难以有效地去除水体、一些深色物体和蓝色地面物体等特征。本文提出了一种基于直方图拟合过程的高分辨率自动阴影提取算法。首先，根据遥感图像中不同阴影区域近红外波段的直方图差异，采用四阶和五阶多项式拟合整幅图像的直方图；其次，根据遥感影像阴影特征与四、五次多项式交点之间的关系，初步提取阴影区域；然后，采用归一化差水指数（NDWI）提取水体。最后，利用扫描线种子填充算法去除在初步阴影提取中被误检为阴影的水体，得到阴影区域。利用高分一号（GF-1）、高分二号（GF-2）、QuickBird2和自源三号（ZY-3）等多种高分辨率图像对算法进行了评价，并与直方图阈值分割算法（Component 3 （C3）算法、多元素提取算法、多波段检测算法和基于光谱特征的光谱相关算法）进行了详细比较。实验结果表明，该算法能够提取各种图像的阴影，取得了满意的效果，能够完全去除水体。
ABSTRACT Most existing shadow detection models and algorithms require extensive calculations and have difficulties effectively removing features, such as water bodies, some dark objects and bluish ground objects. In this paper, we propose a high-resolution automatic shadow extraction algorithm based on the process of histogram fitting. First, the histogram of the whole image is fitted by fourth and fifth-degree polynomials according to the histogram difference of the near-infrared bands of different shadow areas in the remotely sensed image. Second, the shadow area is preliminarily extracted based on the relationships between the shadow features of the remote sensing image and the intersections of the fourth- and fifth-degree polynomials. Then, the normalized difference water index (NDWI) is applied to extract the water bodies. Finally, to obtain the shaded area, the scanning line seed filling algorithm is applied to remove the water bodies falsely detected as shadows in the preliminary shading extraction. The proposed algorithm is evaluated by using the various high-resolution images including GaoFen-1 (GF-1), GaoFen-2 (GF-2), QuickBird2, and ZiYuan-3 (ZY-3), as well as an elaborate comparison to histogram threshold segmentation algorithms such as Component 3 (C3) algorithm, multi-elements extraction algorithm multi-band detection algorithm, and spectral correlation algorithm based on spectral features. The results of experiment showed that the proposed algorithm could extract the shadows of various images, achieve satisfied results, and completely remove water bodies.
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DOI：
10.5194/isprsarchives-xxxix-b3-525-2012
发表时间：
2012-08
期刊：
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
影响因子：
--
作者：
YE Q.;H. Xie;X. Q
通讯作者：
YE Q.;H. Xie;X. Q
城市地区高分辨率遥感图像分类的多指标学习方法
DOI：
10.1016/j.isprsjprs.2014.01.008
发表时间：
2014-04-01
影响因子：
12.7
作者：
Huang, Xin;Lu, Qikai;Zhang, Liangpei
通讯作者：
Zhang, Liangpei
DOI：
--
发表时间：
2013
期刊：
Journal of Lanzhou Jiaotong University
影响因子：
--
作者：
Li Yi-ku
通讯作者：
Li Yi-ku
DOI：
10.1109/jstars.2011.2168195
发表时间：
2012-02-01
影响因子：
5.5
作者：
Huang, Xin;Zhang, Liangpei
通讯作者：
Zhang, Liangpei
DOI：
10.1016/j.isprsjprs.2013.02.003
发表时间：
2013-06-01
影响因子：
12.7
作者：
Adeline, K. R. M.;Chen, M.;Paparoditis, N.
通讯作者：
Paparoditis, N.