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国土资源遥感  2012, Vol. 24 Issue (4): 55-61    DOI: 10.6046/gtzyyg.2012.04.10
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
基于光谱及几何信息的TM图像厚云去除算法
秦雁1, 邓孺孺1, 何颖清1, 陈蕾1,2, 陈启东1, 熊首萍1
1. 中山大学地理科学与规划学院,广州 510275;
2. 国家海洋局南海海洋工程勘察与环境研究院,广州 510300
Algorithm for Removing Thick Clouds in TM Image Based on Spectral and Geometric Information
QIN Yan1, DENG Ru-ru1, HE Ying-qing1, CHEN Lei1,2, CHEN Qi-dong1, XIONG Shou-ping1
1. School of Geographic Science and Planning, Sun Yat-sen University, Guangzhou 510275, China;
2. South China Sea Marine Engineering and Environment Institute, SOA, Guangzhou 510300, China
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摘要 为了去除厚云及其阴影对光学遥感图像的影响,以TM图像为实验数据提出一种基于光谱及几何信息的去厚云算法。在分析单图像云区多光谱特征及对比多时相图像光谱特征的基础上,首先检测光谱特征明显的厚云,依据云和云影成对出现的成像几何关系,按确定的方位和距离搜索云影; 然后采用数学形态学的侵蚀与膨胀算法对云区边缘进行碎片去除及填补、合并处理,使其准确反映图像中受云影响的数据总量; 最后利用光谱线性回归匹配后的参考图像替换目标图像中的云区,达到去云目的。实验结果表明,上述算法去厚云效果显著,能够有效排除水体及地形阴影对云影识别的影响,具有快速、简单、实用性强的特点。
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苏雷
朱京海
胡克梅
刘淼
关键词 城市空间扩展CA模型Logistic回归转移概率矩阵锦葫沿海地区    
Abstract:A new cloud removal algorithm based on spectral and geometric information is proposed for generating cloud free and cloud-shadow free mosaic image from multi-temporal TM images. At first,single image and multi-temporal images of thick cloud and cloud-shadow multi-spectral detection models are built based on TM spectral characteristics analysis. Secondly, cloud is detected according to spectral characteristics,and then a technique is applied based on coupled geometrical relationship between the cloud and its shadow by using sun azimuth angle, sun elevation angle and statistical distance between cloud and its shadow so as to automatically predict the approximate location of cloud-shadow. After that, erosion filtering and dilation filtering are used sequentially in the cloud and cloud-shadow fraction image to eliminate the small bits and generate the exact zones contaminated by cloud and cloud-shadow. At last, the cloud and cloud-shadow zones of the target image are replaced by the same-location cloud-free zones on reference images whose spectral information is matched with the target image by the linear regression method. The results show that this algorithm is capable of eliminating the cloud influence from TM image significantly. Moreover, it can effectively eliminate the influence of water body and hill shadow on cloud-shadow. This method can therefore support producing cloud removal images in a quick, simple and applicable way.
Key wordsurban spatial expansion    CA model    Logistic regression    transition probability matrix    Jinhu coastal area
收稿日期: 2012-03-02      出版日期: 2012-11-13
: 

TP 751.1

 
基金资助:

水利部公益性行业科研专项(编号: 200901067-02)、国家自然科学基金项目(编号: 41071230)和水利部948项目(编号: 200820)共同资助。

通讯作者: 邓孺孺(1963-),男,博士,教授。联系电话: 13925091189; E-mail: eesdrr@mail.sysu.edu.cn。
引用本文:   
秦雁, 邓孺孺, 何颖清, 陈蕾, 陈启东, 熊首萍. 基于光谱及几何信息的TM图像厚云去除算法[J]. 国土资源遥感, 2012, 24(4): 55-61.
QIN Yan, DENG Ru-ru, HE Ying-qing, CHEN Lei, CHEN Qi-dong, XIONG Shou-ping. Algorithm for Removing Thick Clouds in TM Image Based on Spectral and Geometric Information. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(4): 55-61.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2012.04.10      或      https://www.gtzyyg.com/CN/Y2012/V24/I4/55
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