Wavelet Analysis and Its Application in Denoising the Spectrum of Hyperspectral Image
ZHOU Dan1,WANG Qin-jun1,TIAN Qing-jiu2,LIN Qi-zhong1, FU Wen-xue1
1. Center for Earth Observation and Digital Earth,the Chinese Academy of Sciences, Beijing 100086, China 2. International Institute for Earth System Science, Nanjing University, Nanjing 210093, China
摘要: 为了消除高光谱遥感图像中光谱曲线的锯齿型噪声,提高利用光谱曲线进行信息提取研究时的精度,文章使用USGS(united states geological survey)光谱库中的植被光谱进行模拟,添加了信噪比为30的噪声后采用小波阈值法进行噪声去除,并利用信噪比、均方误差和光谱角三项指标以及综合评估系数η来对去噪效果进行评估,寻找出最佳的参数组合。实验表明,使用db12,db10,sym9,sym6等小波对含噪光谱进行3~7层分解,采用软阈值函数处理小波变换系数并使用Heursure阈值方案进行阈值估计,然后根据第一层小波分解的噪声水平估计进行阈值调整可以得到满意的去噪效果。不过该方法对噪声水平有一定的依赖性,针对不同噪声水平时需探索更合适的参数组合。
关键词:高光谱;光谱曲线;噪声去除;小波阈值;MATLAB
Abstract:In order to remove the sawtoothed noise in the spectrum of hyperspectral remote sensing and improve the accuracy of information extraction using spectrum in the present research, the spectrum of vegetation in the USGS (United States Geological Survey) spectrum library was used to simulate the performance of wavelet denoising. These spectra were measured by a custom-modified and computer-controlled Beckman spectrometer at the USGS Denver Spectroscopy Lab. The wavelength accuracy is about 5 nm in the NIR and 2 nm in the visible. In the experiment, noise with signal to noise ratio (SNR) 30 was first added to the spectrum, and then removed by the wavelet denoising approach. For the purpose of finding the optimal parameters combinations, the SNR, mean squared error (MSE), spectral angle (SA) and integrated evaluation coefficient η were used to evaluate the approach’s denoising effects. Denoising effect is directly proportional to SNR, and inversely proportional to MSE, SA and the integrated evaluation coefficient η. Denoising results show that the sawtoothed noise in noisy spectrum was basically eliminated, and the denoised spectrum basically coincides with the original spectrum, maintaining a good spectral characteristic of the curve. Evaluation results show that the optimal denoising can be achieved by firstly decomposing the noisy spectrum into 3-7 levels using db12, db10, sym9 and sym6 wavelets, then processing the wavelet transform coefficients by soft-threshold functions, and finally estimating the thresholds by heursure threshold selection rule and rescaling using a single estimation of level noise based on first-level coefficients. However, this approach depends on the noise level, which means that for different noise level the optimal parameters combination is also diverse.
周丹1,王钦军1,田庆久2,蔺启忠1,傅文学1 . 小波分析及其在高光谱噪声去除中的应用[J]. 光谱学与光谱分析, 2009, 29(07): 1941-1945.
ZHOU Dan1,WANG Qin-jun1,TIAN Qing-jiu2,LIN Qi-zhong1, FU Wen-xue1 . Wavelet Analysis and Its Application in Denoising the Spectrum of Hyperspectral Image. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(07): 1941-1945.
[1] LIU Ming-cai(刘明才). Wavelet Analysis and Its Application(小波分析及其应用). Beijing: Tsinghua University Press(北京: 清华大学出版社), 2005. 125. [2] Donoho D L. IEEE Transactions on Information Theory, 1995, 41(3): 613. [3] LI Qing-wu, CHEN Xiao-gang(李庆武,陈小刚). Optical Technology(光学技术), 2006, 32(6): 831. [4] ZHANG Rong-xiang, LI Zheng-qiang, ZHENG Shi-jie(张荣祥,李正强,郑世杰). Transducer and Microsystem Technologies(传感器与微系统), 2007, 26(6): 20. [5] PAN Zhong-xiao, SUN Pei-yan, WANG Yong-ming, et al(潘忠孝,孙培艳,王永明,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 1999, 19(3): 260. [6] MA Xiao-guo, ZHANG Zhan-xia(马晓国,张展霞). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2003, 23(3): 552. [7] WANG Ying, MO Jin-yuan(王瑛,莫金垣). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(1): 124. [8] HAO Yong, CHEN Bin, ZHU Rui(郝勇,陈斌,朱锐). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(10): 1838. [9] ZOU Xiao-bo, ZHAO Jie-wen, XIA Rong, et al(邹小波,赵杰文,夏蓉,等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2006, 37(6): 79. [10] GUO Hao-yan,HU Shao-ming, QUAN Guang-ri, et al(郭嗥岩,胡绍明,权光日,等). Computer Engineering and Design(计算机工程与设计), 2007, 28(7): 1504. [11] ZHAO Rui-zhen, HU Zhan-yi, HU Shao-hai(赵瑞珍,胡占义,胡绍海). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(8): 1644. [12] DU Yan, LIANG Da-kai(杜艳,梁大开). Chinese Journal of Quantum Electronics(量子电子学报), 2007, 24(3): 294. [13] WU Chuan-qing, TONG Qing-xi, ZHENG Lan-fen(吴传庆,童庆禧,郑兰芬). Remote Sensing Information(遥感信息), 2005, (4): 10. [14] LU Wei, YU Xu-chu, LIU Juan(路威,余旭初,刘娟). Jounral of Information Engineeirng University(信息工程大学学报), 2005, 6(2): 10. [15] Chang S G, Yu B, Vetterli M. IEEE Transactions on Image Processing, 2000, 9(9): 1532. [16] Misiti M, Misiti Y, Oppenheim G, et al. Wavelet Toolbox 4 User’s Guide. Natick, MA: The MathWorks, Inc., 2007.