|Table of Contents|

[1] Xiao Yue, Cui Yiping,. A new kind of wavelet-based method for spectrum deconvolution [J]. Journal of Southeast University (English Edition), 2003, 19 (1): 22-25. [doi:10.3969/j.issn.1003-7985.2003.01.006]
Copy

A new kind of wavelet-based method for spectrum deconvolution()
一种基于小波的光谱反卷积方法
Share:

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
19
Issue:
2003 1
Page:
22-25
Research Field:
Information and Communication Engineering
Publishing date:
2003-03-30

Info

Title:
A new kind of wavelet-based method for spectrum deconvolution
一种基于小波的光谱反卷积方法
Author(s):
Xiao Yue, Cui Yiping
Department of Electronic Engineering, Southeast University, Nanjing 210096, China
肖跃, 崔一平
东南大学电子工程系, 南京 210096
Keywords:
deconvolution slit function wavelet local maxima
反卷积 狭缝函数 小波局部极大值
PACS:
TN911.74
DOI:
10.3969/j.issn.1003-7985.2003.01.006
Abstract:
To subtract the slit function from the measured spectrum, a wavelet-based deconvolution method is proposed to obtain a regularized solution of the problem. The method includes reconstructing the signal from the wavelet modulus maxima. For the purpose of maxima selection, the spatially selective noise filtration technique was used to distinguish modulus maxima produced by signal from the one created by noise. To test the method, sodium spectrum measured at a wide slit was deconvolved. He-Ne spectrum measured at the corresponding slit width was used as slit function. Sodium measured at a narrow slit was used as the reference spectrum. The deconvolution result shows that this method can enhance the resolution of the degraded spectrum greatly.
为消除测量光谱中狭缝宽度的影响, 提出了一种基于小波的反卷积算法以获得问题的规整化解, 该方法使用一维多尺度边缘重构技术.空域选择滤波算法被用来区分由信号产生的极值与由噪声产生的极值.实验中, 对宽狭缝时测得的Na黄光2条特征谱线进行反卷积处理, 以相应狭缝宽度时测得的He-Ne光谱作为狭缝函数, 并与较窄狭缝时测得的 Na光谱作了比较.反卷积结果显示本方法可以极大地提高测量光谱的分辨率.

References:

[1] Zhong Y, Cui Y P, Luo Z N, et al. Research on measurement of luminous flux of discharge lamp with high intensity line spectrum by spectral method [J]. Electron Devices, 1995, 18(2): 98-105.(in Chinese)
[2] Tikhonov A N, Arsenin V Y. Solutions of ill-posed problems[M].New York: Wiley, 1977. 5-30.
[3] Zou M Y. Deconvolution and signal recovery [M].Beijing: Defense Industry Press, 2001. 56-72.(in Chinese)
[4] Avila C S. A nonlinear adaptive wavelet-based method for spiky deconvolution [J]. Nonlinear Analysis, 2001, 47(7): 4937-4948.
[5] Mallat S, Zhong S. Characterization of signal from multiscale edges [J]. IEEE Trans Patt Recog and Mach Intell, 1992, 14(7): 710-732.
[6] Mallat S, Hwang W L. Singularity detection and processing with wavelets[J]. IEEE Trans on Inf Theor, 1992, 38(2):617-643.
[7] Chen Z X. Wavelet analysis algorithm and application [M]. Xi’an: Xi’an Jiaotong University Press, 2000. 209-222.(in Chinese)
[8] Cetin A E, Ansari R. Signal recovery from transform maxima[J]. IEEE Trans on Signal Processing, 1994, 42(1):194-196.
[9] Charalambous C, Ghaddar F K, Kouis K. Two iterative restoration algorithm with application to nuclear medicine[J]. IEEE Trans on Medical Imaging, 1992, 11(1):2-8.
[10] Xu Y, Weaver J B, Healy D M, et al. Wavelet transform domain filters: a spatially selective noise filtration technique[J]. IEEE Trans on Image Processing, 1994, 3(6):747-757.
[11] Pan Q, Zhang L, Dai G Z. Two denoising methods by wavelet transform[J]. IEEE Trans on Signal Processing, 1999, 47(12):3401-3405.

Memo

Memo:
Biographies: Xiao Yue(1978—), male, graduate; Cui Yiping(corresponding author), male, professor, ypcyz@seu.edu.cn.
Last Update: 2003-03-20