| 光谱学与光谱分析 |
|
|
|
|
|
| A Method for Water Body Adaptive Extraction from Remote Sensing Imagery Based on Local End Member Spectral Characterization |
| ZHANG Xin1, ZHU Chang-ming2, LUO Jian-cheng1, LI Wan-qing3, YANG Ji-wei3 |
1. Institute of Remote Sensing Applications, Chinese Academy of Sciences，Beijing 100101，China
2. Department of Geography and Environment，Jiangsu Normal University，Xuzhou 221116，China
3. Heibei University of Enginnering, Handan 056038，China |
|
|
|
|
Abstract Precise spectral characterization is fundamental for thematic information extraction. Because different types of water have different spectral features, which result in the difficulty of automatic retrieving water information precisely from the whole film. The present paper explored a new approach to water adaptive extraction based on local end member spectral characterization (LESC). Firstly, through the spectral index calculation the primary water identification was achieved. Secondly, through spatial analysis and automatic end member extraction, we can get the water end member in part of region. Thirdly, according to the end member spectral, we can calculate local end member spectral similarity and histogram of similarity. Finally，through the histogram spectral analysis the optimal segmentation threshold was determined and according to the results the segmentation threshold was adjusted to fulfill water information extracting automatically and accurately. Experiments results show that through local end member spectral characterization the precision of extraction result can be promoted. The proposed method can extract all types of water information precisely and is not affected by different spectral feature.
|
|
Received: 2012-07-22
Accepted: 2012-10-20
|
|
|
|
Corresponding Authors:
ZHANG Xin
E-mail: zhangx@irsa.ac.cn;ablezhu@163.com
|
|
[1] ZHOU Cheng-hu, DU Yun-yan, LUO Jian-cheng(周成虎, 杜云艳, 骆剑承). Journal of Nature Disasters(自然灾害学报), 1996, 15(3): 100.
[2] McFeeters S K. International Journal of Remote Sensing, 1996, 17(7): 1425.
[3] Paul S F, Kenneth J P. Photogrammetric Engineering & Remote Sensing, 2000, 66(12): 1461.
[4] DING Li-dong, WU Hao，WANG Chang-jian, et al(丁莉东，吴 昊, 王长健). Geomatics & Spatial Information Technology(测绘与空间地理信息), 2006, 29(6): 25.
[5] Liu H, Jezek K C. International Journal of Remote Sensing, 2004, 25(5): 937.
[6] Lira J. International Journal of Remote Sensing, 2006, 27(18): 4015.
[7] Ouma Y O, Tateishi R. International Journal of Remote Sensing, 2006, 27(15): 3153.
[8] XU Han-qiu(徐涵秋). Journal of Remote Sensing(遥感学报), 2005, 9(5): 589.
[9] LUO Jian-cheng, SHENG Yong-wei, SHEN Zhan-feng, et al(骆剑承, 盛永伟, 沈占锋). Journal of Remote Sensing(遥感学报), 2009, 13(4): 610.
[10] Gyanesh Chander, Brian L Markhamb, Dennis L Helder. Remote Sensing of Environment, 2009, 113: 893.
[11] LI Su-mei, WANG Qiao, HUANG Jia-zhu(李素梅, 王 桥, 黄家柱). The Optics Characteristic of Tai Lake Water and Ocean Color Remote Sensing(太湖水体光学特性及水色遥感). Beijing: Science Press(北京：科学出版社), 2010. 06.
[12] Kruse F A, Lefkoff A B, et al. Remote Sensing of Environment, 1993, 44: 145.
[13] Boardman J W, Kruse F A. Nevada: in Proceedings, Tenth Thematic Conference, Geologic Remote Sensing, 9-12 May 1994, San Antonio, Texas, 1994, 407，418. |
| [1] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
| [2] |
WANG Zhen-ni1, KANG Zhi-wei1*, LIU Jin2, ZHANG Jie2. A Solar Spectral Doppler Redshift Velocity Measurement Method Based on Adaptive EMD-NDFT[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3475-3482. |
| [3] |
AN Bai-song1, 2, WANG Xue-mei1, 2*, HUANG Xiao-yu1, 2, KAWUQIATI Bai-shan1, 2. Hyperspectral Estimation of Soil Lead Content Based on Random Frog Band Selection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3302-3309. |
| [4] |
WU Yong-qing1, 2, TANG Na1, HUANG Lu-yao1, CUI Yu-tong1, ZHANG Bo1, GUO Bo-li1, ZHANG Ying-quan1*. Model Construction for Detecting Water Absorption in Wheat Flour Using Vis-NIR Spectroscopy and Combined With Multivariate Statistical #br#
Analyses[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2825-2831. |
| [5] |
LI Zhi1, WANG Xia1*, XU Can1*, LI Peng2, HUO Yu-rong1, FU Jing-yu1, WANG Pei1, FENG Fei3. Review of Spectral Characterization and Identification of Unresolved Space Objects[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1329-1339. |
| [6] |
ZHU Ling, QIN Kai*, SUN Yu, LI Ming, ZHAO Ying-jun. Hyperspectral Unmixing Based on Deep Stacked Autoencoders Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1508-1516. |
| [7] |
ZHANG Fu1, 2, 3, CAO Wei-hua1, CUI Xia-hua1, WANG Xin-yue1, FU San-ling4*, ZHANG Ya-kun1. Non-Destructive Detection of Soluble Solids in Cherry Tomatoes by
Visible/Near Infrared Spectroscopy Based on SG-CARS-IBP[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 737-743. |
| [8] |
XUE Wen-dong1*, CHEN Ben-neng1, HONG De-ming1, YANG Zhen-hai1, LIU Guo-kun2. Research on Raman Spectrum Recognition Method Based on Improved
Reverse Matching[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 753-759. |
| [9] |
WANG Ren-jie1, 2, FENG Peng1*, YANG Xing3, AN Le3, HUANG Pan1, LUO Yan1, HE Peng1, TANG Bin1, 2*. A Denoising Algorithm for Ultraviolet-Visible Spectrum Based on
CEEMDAN and Dual-Tree Complex Wavelet Transform[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 976-983. |
| [10] |
LI Qing-bo1, BI Zhi-qi1, CUI Hou-xin2, LANG Jia-ye2, SHEN Zhong-kai2. Detection of Total Organic Carbon in Surface Water Based on UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3423-3427. |
| [11] |
DUAN Hong-wei1, 2, GUO Mei3, ZHU Rong-guang3, NIU Qi-jian1, 2. LIBS Quantitative Analysis of Calorific Value of Straw Charcoal Based on XY Bivariate Feature Extraction Strategy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3435-3440. |
| [12] |
HU Yun-you1, 2, XU Liang1*, XU Han-yang1, SHEN Xian-chun1, SUN Yong-feng1, XU Huan-yao1, 2, DENG Ya-song1, 2, LIU Jian-guo1, LIU Wen-qing1. Adaptive Matched Filter Detection for Leakage Gas Based on Multi-Frame Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3307-3313. |
| [13] |
ZHONG Xiang-jun1,2, YANG Li1,2*, ZHANG Dong-xing1,2, CUI Tao1,2, HE Xian-tao1,2, DU Zhao-hui1,2. Prediction of Organic Matter Content in Sandy Fluvo-Aquic Soil by
Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2924-2930. |
| [14] |
ZHONG Xiang-jun1, 2, YANG Li1, 2*, ZHANG Dong-xing1, 2, CUI Tao1, 2, HE Xian-tao1, 2, DU Zhao-hui1, 2. Effect of Different Particle Sizes on the Prediction of Soil Organic Matter Content by Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2542-2550. |
| [15] |
JIANG Xiao-yu1, 2, LI Fu-sheng2*, WANG Qing-ya1, 2, LUO Jie3, HAO Jun1, 2, XU Mu-qiang1, 2. Determination of Lead and Arsenic in Soil Samples by X Fluorescence Spectrum Combined With CARS Variables Screening Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1535-1540. |
|
|
|
|
