Semi-automatic Landslide Extraction for Remote Sensing Image Based on Spectral Matting

doi:10.3969/j.issn.1000-3428.2012.02.064

Computer Engineering ›› 2012, Vol. 38 ›› Issue (2): 195-197. doi: 10.3969/j.issn.1000-3428.2012.02.064

• Networks and Communications • Previous Articles Next Articles

Semi-automatic Landslide Extraction for Remote Sensing Image Based on Spectral Matting

WANG Shi-bo ^a, ZHANG Da-ming ^a, LUO Bin ^a, ZHANG Chun-yan ^b

(a. Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education; b. School of Mathematical Sciences, Anhui University, Hefei 230039, China)

Received:2011-07-11 Online:2012-01-20 Published:2012-01-20

基于谱抠图的遥感图像滑坡半自动提取

王世博 ^a，张大明^a，罗斌 ^a，张春燕^b

(安徽大学 a. 计算智能与信号处理教育部重点实验室；b. 数学科学学院，合肥 230039)

作者简介:王世博(1984－)，男，硕士研究生，主研方向：数字图像处理，模式识别；张大明，讲师、博士研究生；罗斌，教授、博士生导师；张春燕，副教授、博士
基金资助:
国家自然科学基金资助项目(60772122)；高等学校博士学科点专项科研基金资助项目(20070357001)；安徽省高校优秀青年人才基金资助项目(2010SQRL093)；安徽省高校自然科学科研基金资助项目(KJ2010A326)

Abstract

Abstract: In order to calculate the landslide areas from remote sensing image, a semi-automatic algorithm for extracting the landslide is proposed based on spectral matting. Matting Laplacian matrix is established to calculate feature vector, automatically determine the number of clusters, and hill-climbing algorithm is used for clustering image. Matting components are calculated based on feature vector and the user’s data. The smoothing term is removed, and alpha is got. Experimental results show that the method can effectively extract the landslide, performs high accuracy and strong stability.

Key words: remote sensing image, landslide extraction, Laplacian matrix, spectral matting, hill-climbing algorithm

摘要： 为统计遥感图像中滑坡区域的有效数据，提出基于谱抠图的遥感图像滑坡半自动提取方法。建立抠图拉普拉斯矩阵，计算特征向量，自动确定聚类数，利用爬山算法对图像聚类，根据特征向量和用户交互数据得到抠图成分，去除平滑项，得到前景透明度。实验结果证明该方法能够有效提取滑坡信息，准确率高，稳定性强。

关键词: 遥感图像, 滑坡提取, 拉普拉斯矩阵, 谱抠图, 爬山算法

CLC Number:

TP391.41

WANG Shi-Bo, ZHANG Da-Meng, LUO Bin, ZHANG Chun-Yan. Semi-automatic Landslide Extraction for Remote Sensing Image Based on Spectral Matting[J]. Computer Engineering, 2012, 38(2): 195-197.

王世博, 张大明, 罗斌, 张春燕. 基于谱抠图的遥感图像滑坡半自动提取[J]. 计算机工程, 2012, 38(2): 195-197.

/ / Recommend / Download Citations

URL: http://www.ecice06.com/EN/10.3969/j.issn.1000-3428.2012.02.064

http://www.ecice06.com/EN/Y2012/V38/I2/195

[1]	PANG Tao, ZHANG Xuemin, YAO Yazhou, GAO Mingke. Optical Remote Sensing Image Building Change Detection Based on Feature Enhancement [J]. Computer Engineering, 2023, 49(4): 182-187.
[2]	HE Yue, CHEN Guangsheng, JING Weipeng, XU Zekun. Remote Sensing Image Retrieval Based on Deep Multi-Similarity Hashing Method [J]. Computer Engineering, 2023, 49(2): 206-212.
[3]	LI Linke, KANG Zhao, LONG Bo. Riemannian Manifold Based Multi-View Spectral Clustering Algorithm [J]. Computer Engineering, 2023, 49(1): 113-120,129.
[4]	HE Xiaohui, SONG Dingjun, LI Panle, TIAN Zhihui, ZHOU Guangsheng. Remote Sensing Image Road Extraction Method Combined with Multi-Scale Features [J]. Computer Engineering, 2022, 48(8): 196-205.
[5]	WANG Daolei, DU Wenbin, LIU Yiteng, ZHANG Tianyu, SUN Jiajun, LI Mingshan. Remote Sensing Images Detection Based on Dense Connection and Feature Enhancement [J]. Computer Engineering, 2022, 48(6): 251-256,262.
[6]	XIE Shuchun, CHEN Zhihua, SHENG Bin. Detail-Enhanced RGB-IR Multichannel Feature Fusion Network for Semantic Segmentation [J]. Computer Engineering, 2022, 48(10): 230-237,244.
[7]	ZHANG Yan, DU Huijuan, SUN Yemei, LI Xianguo. Object Detection in Remote Sensing Images Based on Improved SSD Algorithm [J]. Computer Engineering, 2021, 47(9): 252-258,265.
[8]	ZHANG Liheng, WANG Hao, XUE Bowei, HE Liming, Lü Yue. Research of Road Extraction from High-Resolution Remote Sensing Images Based on Improved D-LinkNet Model [J]. Computer Engineering, 2021, 47(9): 288-296.
[9]	HE Xiaohui, LI Daidong, LI Panle, HU Shaokai, CHEN Mingyang, TIAN Zhihui, ZHOU Guangsheng. Road Extraction from High-Resolution Remote Sensing Images Based on EDRNet Model [J]. Computer Engineering, 2021, 47(9): 297-303,312.
[10]	CHEN Huiwei, LIU Shumei, LIU Peixue, GONG Maofa. Remote Sensing Ship Recognition Based on Hyper-Scale Self-Guided Attention Networks [J]. Computer Engineering, 2021, 47(10): 314-320.
[11]	BAO Yintu, LIU Wei, NIU Chaoyang, LI Runsheng, ZHANG Haobo. Scene Classification of Optical Remote Sensing Images Joint Ensemble Learning and EfficientNet [J]. Computer Engineering, 2021, 47(10): 226-235.
[12]	LIU Xuan, CHI Mingmin. Scene Classification Research for Remote Sensing Images Based on Multi?Granularity Feature Distillation [J]. Computer Engineering, 2021, 47(1): 224-229,238.
[13]	LI Wenbin, HE Ran. Aircraft Target Detection of Remote Sensing Images Based on Deep Neural Network [J]. Computer Engineering, 2020, 46(7): 268-276.
[14]	BAO Zhuangzhuang, ZHAO Xuejun, WANG Mingfang, DONG Yuhao, PANG Mengyang, HUANG Lin, HE Gang. Multi-Scale Target Detection Network Model Trained from Scratch [J]. Computer Engineering, 2020, 46(6): 248-255.
[15]	LIANG Wentao, KANG Yan, LI Hao, LI Jinyuan, NING Haoyu. Adaptive Remote Sensing Scene Classification Based on Complexity Clustering [J]. Computer Engineering, 2020, 46(12): 254-261,269.

Please choose a citation manager

Content to export

Semi-automatic Landslide Extraction for Remote Sensing Image Based on Spectral Matting

基于谱抠图的遥感图像滑坡半自动提取

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

模态框（Modal）标题

Please choose a citation manager

Content to export

Semi-automatic Landslide Extraction for Remote Sensing Image Based on Spectral Matting

基于谱抠图的遥感图像滑坡半自动提取

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments