| 光谱学与光谱分析 |
|
|
|
|
|
| A Novel Wavelet Multiple Thresholding Algorithm for Astronomical Spectral Signal Denoising |
| ZHAO Rui-zhen1,HU Zhan-yi2,HU Shao-hai1 |
1. School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China
2. National Key Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100080,China |
|
|
|
|
Abstract By using the different relativities of spectral lines and noises in the wavelet domain,a novel wavelet multiple thresholding algorithm is presented in the present paper for astronomical spectra with low signal-noise-ratio (SNR). Firstly the wavelet coefficients are estimated by NeighShrink approach and then 0-1 coefficients are obtained. Based on the above binary coefficients,two kinds of relativity exponents at each scale and across scales respectively are defined for each wavelet coefficients. Finally decision coefficients are determined according to the magnitudes of the relativity exponents. This algorithm overcomes the over-reserving or over-shrinking disadvantages of the simple threshold method in that the decision coefficients are obtained by multiple criteria. Besides,large pulse noises can be removed by the presented algorithm because it takes spectral line features into consideration. The experimental results show that the proposed algorithm is computationally efficient and practical.
|
|
Received: 2006-04-20
Accepted: 2006-07-25
|
|
|
|
Corresponding Authors:
ZHAO Rui-zhen
E-mail: rzhzhao@bjtu.edu.cn
|
|
| Cite this article: |
|
ZHAO Rui-zhen,HU Zhan-yi,HU Shao-hai. A Novel Wavelet Multiple Thresholding Algorithm for Astronomical Spectral Signal Denoising[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(08): 1644-1647.
|
|
|
|
| URL: |
|
http://www.gpxygpfx.com/EN/Y2007/V27/I08/1644 |
[1] ZHAO Rui-zhen,HU Zhan-yi,ZHAO Yong-heng(赵瑞珍，胡占义，赵永恒). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2005,25(1): 153.
[2] LIU Rong,LIU San-yang,ZHAO Rui-zhen(刘 蓉，刘三阳，赵瑞珍). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2006，26(3)： 583.
[3] ZHAO Rui-zhen,LUO A-li(赵瑞珍，罗阿理). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2006，26(3)： 587
[4] Mallat S,Zhong S. IEEE Trans on Pattern Anlysis and Machine Intelligence(PAMI),1992,14(7): 710.
[5] Mallat S,Hwang W L. IEEE Trans on IT,1992,38(2): 617.
[6] Xu Y,Weaver J,Healy M,et al. IEEE Trans. on IP,1994,3(6): 747.
[7] Pan Q,Zhang L,Dai G,et al. IEEE Trans. on SP.,1999,47(12): 3401.
[8] Donoho D L. IEEE Trans on IT,1995,41(3): 613.
[9] Donoho D L,Johnstone I M. Biometrika,1994,81: 425.
[10] Pizurica A,Philips W,Lemahieu I,et al. IEEE Trans. on IP,2002,11(5): 545.
[11] Balster E J,Zheng Y F,Ewing R L. IEEE Trans. on IP,2005,14(12): 2024.
[12] Cai T T,Silverman B W. The Indian Journal of Statistics,2001,63(B): 127.
[13] Chen G Y,Bui T D,Krzyzak A. ICASSP 2004,Ⅱ: 917.
[14] Zhao R Z,Hu Z Y. ICSP’06 Proceedings,2006,1: 314.
[15] ZHAO Rui-zhen,HU Zhan-yi(赵瑞珍，胡占义). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2007,27(1): 198. |
| [1] |
JIANG Rong-chang1, 2, GU Ming-sheng2, ZHAO Qing-he1, LI Xin-ran1, SHEN Jing-xin1, 3, SU Zhong-bin1*. Identification of Pesticide Residue Types in Chinese Cabbage Based on Hyperspectral and Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1385-1392. |
| [2] |
WANG Zhong, WAN Dong-dong, SHAN Chuang, LI Yue-e, ZHOU Qing-guo*. A Denoising Method Based on Back Propagation Neural Network for
Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1553-1560. |
| [3] |
LI Xue-ying1, 2, LI Zong-min3*, CHEN Guang-yuan4, QIU Hui-min2, HOU Guang-li2, FAN Ping-ping2*. Prediction of Tidal Flat Sediment Moisture Content Based on Wavelet Transform[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1156-1161. |
| [4] |
Yumiti Maiming1, WANG Xue-mei1, 2*. Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1278-1284. |
| [5] |
ZHU Hong-qiu1, CHENG Fei1, HU Hao-nan1, ZHOU Can1, 2*, LI Yong-gang1. Denoising Algorithm of Spectral Signal Based on FFT SVD[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 277-281. |
| [6] |
JIAO Qing-liang1, LIU Ming1*, YU Kun2, LIU Zi-long2, 3, KONG Ling-qin1, HUI Mei1, DONG Li-quan1, ZHAO Yue-jin1. Spectral Pre-Processing Based on Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 292-297. |
| [7] |
CHEN Feng-nong1, SANG Jia-mao1, YAO Rui1, SUN Hong-wei1, ZHANG Yao1, ZHANG Jing-cheng1, HUANG Yun2, XU Jun-feng3. Rapid Nondestructive Detection and Spectral Characteristics Analysis of Factors Affecting the Quality of Dendrobium Officinale[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3276-3280. |
| [8] |
CHEN Jian-hong, LIN Zhi-qiang, SUN Chao-yue. Determination of New Non-Invasive Blood Glucose Detection Method Based on Spectral Decomposition[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(08): 2378-2383. |
| [9] |
WU Lian-hui1, 2, 3, HE Jian-feng1, 2, 3*, ZHOU Shi-rong2, 3, WANG Xue-yuan1, 2, YE Zhi-xiang2, 3. A Multi-Derivation-Spline Wavelet Analysis Method for Low Atomic Number Element EDXRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(08): 2530-2535. |
| [10] |
YANG Bao-hua1, GAO Yuan1, WANG Meng-xuan1, QI Lin1, NING Jing-ming2. Estimation Model of Polyphenols Content in Yellow Tea Based on Spectral-Spatial Features[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(03): 936-942. |
| [11] |
ZHENG Hai-ming, ZHU Xiao-peng, FENG Shuai-shuai, JIA Gui-hong. Experimental Research on Monitoring of BTX Concentration Based on Differential Optical Absorption Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(02): 467-472. |
| [12] |
WANG Xue-yuan1, 2, 3, HE Jian-feng1, 2, 3*, LIU Lin1, 2, 3, NIE Feng-jun2. Research on Adaptive Peak Detection of X-Ray Fluorescence Spectrum With Wavelet Transform and Derivative Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3930-3935. |
| [13] |
QIU Rong-chao1, LÜ Jun-wei1, GONG Jian1, LOU Shu-li2, XIU Bing-nan1, MA Xin-xing1. Smoothing Method for Sea Surface Rough Background Based on Multi-Spectral Forward-Looking Infrared Images Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(04): 1120-1126. |
| [14] |
ZHOU Shi-rong2,3, HE Jian-feng1,2,3*, REN Yin-quan2,3, WANG Xue-yuan1,2, YE Zhi-xiang2,3. Research on a Decomposing Method of Low-Resolution Overlapping Peaks in X-Ray Fluorescence Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(04): 1221-1226. |
| [15] |
LI Hang-fei, TU Liang-ping*, HU Yu-han, LIU Hao, ZHAO Jian. Automatic Measurement of Stellar Atmospheric Physical Parameters Based on Kernel Ridge Regression Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(04): 1297-1303. |
|
|
|
|
