[1]韦玉春,王国祥,程春梅,等.水面光谱数据的核回归平滑去干扰分析[J].南京师大学报(自然科学版),2010,33(03):97-102.
　Wei Yuchun,Wang Guoxiang,Cheng Chunmei.Noise Removal in Spectrum Above Water Surface Using Kernel Regression Smoothing[J].Journal of Nanjing Normal University(Natural Science Edition),2010,33(03):97-102.
点击复制

水面光谱数据的核回归平滑去干扰分析()
分享到：

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第33卷
期数:
2010年03期
页码:
97-102
栏目:
地理学
出版日期:
2010-09-20

文章信息/Info

Title:
Noise Removal in Spectrum Above Water Surface Using Kernel Regression Smoothing
作者:
韦玉春;王国祥;程春梅;
南京师范大学虚拟地理环境教育部重点实验室, 江苏南京210046
Author(s):
Wei Yuchun; Wang Guoxiang; Cheng Chunmei
Key Lab of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University,Nanjing 210046,China
关键词:
核回归;  平滑;  信扰比;  蒙特卡洛模拟;  水面光谱;  遥感
Keywords:
kerne l regress ion;  sm oo th;  signa l to interference ratio;  monte-car lo s imu la tion;  spectrum above w ater surface;  remo te sensing
分类号:
TP79
摘要:
水面光谱是利用遥感反演水体水质参数的数据基础, 去除光谱中的噪声干扰, 提高光谱的信号干扰比有助于改进水质参数的遥感反演的精度. 本文选择叶绿素a浓度相同而悬浮泥沙浓度差异较大的两个水面光谱为代表, 分析了核回归平滑方法对干扰的去除效果. 假定干扰类型为4类, 分别是正态分布、瑞利分布、指数分布和泊松分布, 设定的干扰强度分为4级. 利用蒙特卡洛模拟方法, 通过500轮次的模拟计算了核回归平滑前后水面光谱的信号干扰比, 并与多项式平滑、移动平均、局部回归和鲁棒性的局部回归平滑方法进行了比较. 结果表明, 不论干扰强度高或低, 核回归平滑后的光谱均具有最高的信号干扰比. 在四类干扰中, 核回归平滑对于正态分布的干扰去除效果较好. 与常用的多项式平滑方法相比, 核回归平滑方法比较完整地保留了水面光谱中的峰谷位置信息, 是一种值得推荐的提高水面光谱信号干扰比的方法.
Abstract:
Spec trum above w ater surface w ith h igh signa l to inte rference ra tio ( SIR) is the key to estima tew ate r qua lity param eters by rem ote sensing. To decrease inte rference and increase SIR of spectrum is the important content o f spectrum ana lysis. In th is paper, tw o spectrum above wa ter surface, wh ich ch lorophy l-l a concentra tion is sam e and suspended substance concentration is different, was taken as exam ples to ana lysis the de-no ising e ffect o f the kernel regression sm ooth ing. The paper uses theM onte-Car lo simu la tion m ethod to estim ate the average o f S IR by 500 rounds, g iven four interference disturbance type, .i e. Norm a l d istr ibu te, Ray leigh distribute, Exponentia l d istr ibute and Po isson d istr ibute, and four interference intensity. The SIR of ke rnel reg ression sm oothing were also com pa red w ith that o f Sav itzky-Golay smoo th filter, m ov ing av erage, loca l regression and robust lo ca l regress ion. The resu lt shows tha t kerne l regression sm ooth ing not on ly increases the SIR of spectrum, but also has the h ighest SIR than o ther fourme thods whether the interference intens ity is h igher or low er. SIR is the h ighest when interference is o f the norm a l distribute. Com pa re w ith Savitzky-Go lay sm ooth filter, the spectrum by kerne l regress ion sm ooth ing w asm ore smoo ther and keptm ore inform ation on spectrum  s peak and va lley position. The paper conc ludes tha t kerne l regress ion sm ooth ing is a be tterm e thod to dec rease in terference influence in the spectrum abovew ate r sur face.

参考文献/References:

[ 1]ArstH. Optical Properties and Remo te Sensing ofMu lticomponentalW ater Bod ies[M ]. Chichester: Springer, Prax is Pub lishing, 2003.
[ 2]Analytical Spectra lDev ices Inc. Fie ldSpec Pro Use r?? s Guide[M ]. Boulder: Analytical Spectra lDev ices Inc, 2002.
[ 3]郑咏梅, 张铁强. 平滑、导数、基线校正对近红外光谱PLS定量分析的影响研究[ J]. 光谱学与光谱分析, 2004, 24 ( 12): 1 546-1 548.
[ 4]倪永年. 化学计量学在分析化学中的应用[M ]. 北京: 科学出版社, 2005.
[ 5]Bowm an A W, Azza lini A. Applied Smoo th ing Techn iques fo rData Ana lysis[M ] . New York: Ox ford Un iversity Press, 1997.
[ 6]郭波涛, 易东, 王文昌. 核平滑半参数回归模型在重复测量资料中的应用[ J]. 中国卫生统计, 2007, 24( 5) : 456-458.
[ 7]唐军武, 田国良, 汪小勇, 等. 水体光谱测量与分析Ⅰ : 水面以上测量法[ J] . 遥感学报, 2004, 8( 1): 37-44.
[ 8]Bosco lo, Pan R H, Roychowdhury V P. Independent Com ponen t Ana lys is Based on Nonpa ram e tric Dens ity Estim ation[ J]. IEEE Trans on Neura lNe tw orks, 2004, 15( 1): 55-65.
[ 9]Y i Cao. K ernel Sm oothing Regression, 2008[ EB /OL]. [ 2009-03-28 ]. http: / /www. m athw orks. com /ma tlabcentral/ fileexchange /19195-kerne-l sm ooth ing- reg ression.
[ 10]Nadaraya E A. On estim ating reg ression[ J]. Theo ry o f Probability and its App lications, 1964, 9( 1): 141-142.

备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 40771152)、江苏省普通高校自然科学研究计划资助项目( 07KJB420062) . 通讯联系人: 韦玉春, 博士, 教授, 研究方向: 环境遥感. E-mail:weiyuchun@ njnu. edu. cn
更新日期/Last Update: 2013-04-08