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Blind deconvolution using the similarity of multiscales regularization for infrared spectrum

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成果类型:
期刊论文
作者:
Huang, Tao*;Liu, Hai;Zhang, Zhaoli;Liu, Sanyan;Liu, Tingting;...
通讯作者:
Huang, Tao
作者机构:
[Shen, Xiaoxuan; Liu, Sanyan; Liu, Tingting; Zhang, Jianfeng; Zhang, Zhaoli; Huang, Tao; Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
[Zhang, Tianxu] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China.
通讯机构:
[Huang, Tao] C
Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Convolution;Deconvolution;Digital signal processing;Spectroscopy;Blind deconvolution;Infrared spectral;Infrared spectrum;multiscales;Spectral deconvolution;Spectral feature;State-of-the-art methods;Super resolution;Signal processing
期刊:
Measurement Science And Technology
ISSN:
0957-0233
年:
2015
卷:
26
期:
11
页码:
115502
基金类别:
National Social Science Fund of China [14BGL131]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61505064, 60902060]; Project of the Program for the National Key Technology Research and Development Program [2013BAH72B01, 2013BAH18F02, 2015BAH33F02, 2015BAK07B03]; Self-Determined Research Funds of CCNU from the Colleges' Basic Research and Operation of MOE [CCNU15A05059, CCNU15A05009, CCNU15A05010]; Scientific R&D Project of State Education Ministry and China Mobile [MCM20121061]; New PhD Researcher Award from the Chinese Ministry of EducationMinistry of Education, China; New Century Excellent Talents in UniversityProgram for New Century Excellent Talents in University (NCET) [NCET-11-0654]
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Band overlap and random noise exist widely when the spectra are captured using an infrared spectrometer, especially since the aging of instruments has become a serious problem. In this paper, via introducing the similarity of multiscales, a blind spectral deconvolution method is proposed. Considering that there is a similarity between latent spectra at different scales, it is used as prior knowledge to constrain the estimated latent spectrum similar to pre-scale to reduce artifacts which are produced from deconvolution. The experimental results indicate that the proposed method is able to obta...

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