电光与控制, 2016, 23 (6): 30, 网络出版: 2021-01-28  

一种针对光谱匹配的高光谱图像预处理方法

A Hyperspectral Image Preprocessing Method for Spectral Matching
作者单位
火箭军工程大学,西安710025
摘要
光谱匹配对光谱曲线的稳定性和准确性均有严格要求,而高光谱图像数据中的光谱曲线受多种因素影响。对此,以平场域法为基础,设计了自动搜索平场域策略,并结合黑暗像元法和其他研究领域常用的经验法,提出一种改进的高光谱图像预处理方法,实现了基于高光谱图像本身数据的自动反射率反演。使用3幅各具特点的图像数据进行的实验表明,本文方法比传统的内部平均法和平场域法有更强的准确性和鲁棒性,能有效改善光谱匹配的效果。
Abstract
Spectral matching has strict requirements to stability and accuracy of the spectral curve, while the spectral curve in hyperspectral image data is influenced by many factors. An automatic search flat field strategy is designed based on the flat field method. An improved preprocessing method is proposed for hyperspectral images on the basis of dark-object subtraction and empirical method commonly used in the other research areas. Thus automatic reflectance inversion based on hyperspectral image data is realized. Experiments using three different images show that the method of this paper is more accurate and robust than the traditional methods, and can effectively improve the effect of spectral matching.
参考文献

[1] 李薇薇. 高光谱数据库的地物特征反演研究[D]. 武汉:华中师范大学, 2012. (LI W W. Inversion researches of surface features based on hyperspectral databases[D]. Wuhan:Huazhong Normal University, 2012. )

[2] 陈克清. 迷彩伪装服的高光谱特性研究[D]. 上海:东华大学, 2014. (CHEN K Q. Research on hyperspectral characteristic of camouflage clothing[D]. Shanghai:Donghua University,2014. )

[3] 孙旭光. 基于高光谱图像目标探测与分类技术研究[D]. 北京:中国科学院研究生院, 2013. (SUN X G. Target detection and classification based on hyperspectral image[D]. Beijing:University of Chinese Academy of Sciences, 2013. )

[4] LI S S, ZHANG B, GAO L R, et al. Research of hyperspectral target detection algorithms based on variance minimum[J]. Acta Optica Sinica, 2010, 30(7): 2116-2122.

[5] 范冬娟, 张韶华. 高光谱反射率反演方法的研究[J]. 海洋测绘, 2006, 26(3): 28-30. (FAN D J, ZHANG S H. Research on the methods of the reflectivity inversion of the high spectrum image[J]. Hydrographic Surveying and Charting, 2006, 26(3): 28-30. )

[6] ELVIDGE C D, CHEN Z K, GROENEVELD D P. Detection of trace quantities of green vegetation in 1990 AVIRIS data[J]. Remote Sensing of Environment, 1993, 44(2/3): 271-279.

[7] 何立明, 阎广建, 王桥,等. 光学遥感大气订正模型及相关问题分析[J]. 地球信息科学, 2005, 7(4): 33-38. (HE L M, YAN G J, WANG Q, et al. Atmospheric correction model and analysis of related problems of remote sensing[J]. Geo-information Science, 2005, 7(4): 33-38. )

[8] 田庆久, 郑兰芬, 童庆禧. 基于遥感影像的大气辐射校正和反射率反演方法[J]. 应用气象学报, 1998, 9(4): 456-461. (TIAN Q J, ZHENG L F, TONG Q X. Atmospheric radiation correction and reflectance inversion me-thod based on remote sensing image[J]. Quarterly Journal of Applied Meteorology, 1998, 9(4): 456-461. )

[9] 张兵. 时空信息辅助下的高光谱数据挖掘[D]. 北京:中国科学院遥感应用研究所,2002. (ZHANG B. Hyperspectral data mining supported by temporal and spatial information[D]. Beijing:Institute of Remote Sensing Application CAS, 2002. )

[10] GORDON H R. Removal of atmospheric effects from sa-tellite imagery of the ocean[J]. Applied Optics, 1978, 17(13): 1631-1636.

[11] AHERN F J, GOODENOUGH D G, JAIN S C, et al. Use of clear lakes as standard reflectors for atmospheric measurements[C]//Proceedings of the 11th International Symposium on Remote Sensing of Environment, 1977:731-775.

[12] 余旭初, 冯五法, 杨国鹏, 等. 高光谱影像分析与应用[M]. 北京: 科学出版社,2013: 54. (YU X C, FENG W F, YANG G P, et al. The analysis and application of highspectral image[M]. Beijing: Science Press, 2013: 54. )

[13] 许卫东, 尹球, 匡定波. 地物光谱匹配模型比较研究[J]. 红外与毫米波学报, 2005, 4(4): 296-300. (XU W D, YIN Q, KUANG D B. Comparison of different spectral match models[J]. Journal of Infrared and Millimeter Waves, 2005, 4(4): 296-300. )

刘志刚, 刘翔, 廖佳俊, 蔡尚. 一种针对光谱匹配的高光谱图像预处理方法[J]. 电光与控制, 2016, 23(6): 30. LIU Zhi-gang, LIU Xiang, LIAO Jia-jun, CAI Shang. A Hyperspectral Image Preprocessing Method for Spectral Matching[J]. Electronics Optics & Control, 2016, 23(6): 30.

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