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遥感技术与应用  2018, Vol. 33 Issue (3): 563-572    DOI: 10.11873/j.issn.1004-0323.2018.3.0563
数据与图像处理     
基于亮度恢复模型的Landsat 8数据山区阴影去除
赖日文1,池毓锋1,张泽均2
(1.福建农林大学林学院,福建 福州 350002;
2.福建农林大学计算机与信息学院,福建 福州 350002)
Landsat 8 Data Mountain Shadow Removal based onBrightness Recovering Model
Lai Riwen1,Chi Yufeng1,Zhang Zejun2
(1.College of Forestry,Fujian Agriculture and Forestry University,Fuzhou 350002,China;
2.College of Computer and Information Sciences,Fujian Agriculture and Forestry University,Fuzhou 350002,China)
 全文: PDF(12610 KB)  
摘要:
遥感影像中的山区阴影覆盖范围广、去除难度大、影响信息提取精度,通过最大值选取函数(Max)与波段比值构建阴影检测模型(Shadow Detection,SD),结合坡度因子提取影像中山地阴影区域,并通过网格随机布置验证点验证精度;通过地面阴影亮度与阴影像元亮度变化规律,拟合影像阴影区亮度曲线模型,结合导函数,建立亮度恢复模型。对长汀县域的Landsat 8影像处理,获得的结果显示:山区阴影的提取精度为99.06%,Kappa系数为98%;聚类显示恢复区与非阴影属于同一类型;通过亮度恢复模型计算得出各个波段的阴影区域像元亮度平均值提升13%,标准差降低80%,距离系数降低96%,较ATCOR_3方法,像元亮度平均值提升6.7%,标准差降低73.7%,距离系数降低88.3%,较一元线性恢复方法,像元亮度平均值降低1.8%,标准差提升6.7%,距离系数降低90%。该方法在恢复山区阴影的过程中实现了不替换阴影像元,不干扰非阴影像元,能较好地保留阴影像元的光谱与亮度特征。
 
关键词: Max函数导函数阴影提取阴影恢复聚类分析    
Abstract: Mountain region in remotely sensed imagery are usually covered by shadows,which reduce the accuracy of information extraction.Therefore,in this paper a method based on intensity restoration is putting forward necessarily.First,Shadow Detection (SD) was constructed by the Max function and the band ratio to identify shadows.Thus,mountain shadows were extracted combined with the slope factor and SD,through the grid randomly arranged verification point verification accuracy.Second,the intensity curve model of the shadow area was fitted by ground data of the shadow and the transition rules of pixel intensity from the shadow to non\|shaded area.Third,the intensity restoration model was established by the derivative function of intensity curve to remove shadows.The results of the model on Changting Landsat 8 imagery indicated the extraction accuracy of the mountain shadow was 99.06% and the Kappa coefficient was 98%;According to the cluster analysis,the restoration and non\|shaded samples were the same type;Processed by the intensity restoration model,the average intensity of the shadow was increased by 13%,and the standard deviation was reduced by 80% and the clustering distances was reduced by 96%.respectively,average intensity of the shadow increased by 6.7%,the standard deviation was reduced by 73.7% and the clustering distances was reduced by 88.3% when compared with ATCOR_3,and average intensity of the shadow reduced by 1.8%,the standard deviation was increased by 6.7% and the clustering distances was reduced by 90% when compared with unitary linear restoration model.In the process of removing the mountain shadows,the intensity restoration method is neither replacing the shaded pixels nor interference with non\|shaded pixels and could preserve the spectral and intensity characteristics of shaded pixels better.


Key words: Max function    Derived function    Shadow extraction    Shadow removal    Cluster analysis.
收稿日期: 2017-07-30 出版日期: 2018-07-04
:  TP 79  
基金资助: 生态林种科研基地建设工程项目(61201400814),福建省自然科学基金项目“融合边缘和区域特征的高分辨SAR图像快速分割算法研究”(2016J01753)资助
作者简介: 赖日文(1970-),男,福建政和人,博士,副教授,主要从事3S技术研究。 Email:fjlrw@126.com。
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引用本文:

赖日文,池毓锋,张泽均. 基于亮度恢复模型的Landsat 8数据山区阴影去除[J]. 遥感技术与应用, 2018, 33(3): 563-572.

Lai Riwen,Chi Yufeng,Zhang Zejun. Landsat 8 Data Mountain Shadow Removal based onBrightness Recovering Model. Remote Sensing Technology and Application, 2018, 33(3): 563-572.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2018.3.0563        http://www.rsta.ac.cn/CN/Y2018/V33/I3/563

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