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Spectral restoration using semi-blind deconvolution method with detail-preserving regularization
Institution:1. Grupo de Lactamas y Heterociclos Bioactivos, Departamento de Química Orgánica, Unidad Asociada al CSIC, Facultad de Química, Universidad Complutense de Madrid, 28040-Madrid, Spain;2. Departamento de Química Orgánica and Centro de Innovación en Química Avanzada (ORFEO-CINQA), Facultad de Química, Universidad Complutense de Madrid, 28040-Madrid, Spain;3. Instituto de Química Orgánica General, IQOG, CSIC, Juan de la Cierva 3, 28006-Madrid, Spain;1. Graduate School of Science and Technology, Shizuoka University, 3-5-1 Johoku, Nakaku, Hamamatsu 432-8011, Japan;2. Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI Depok, Depok 16424, Indonesia;3. Department of Mechanical Engineering, Graduate School of Engineering, Shizuoka University, 3-5-1 Johoku, Nakaku, Hamamatsu 432-8011, Japan;1. Department of Mechanical Engineering Education, Universitas Negeri Sebelas Maret, Jl. Ahmad Yani 200A, Pabelan, Indonesia;2. Energy Resources Engineering Laboratory, Department of Earth Resources Engineering, Kyushu University, 744 Motooka, Nishi-ku, 819-0395 Fukuoka, Japan;3. Department of Energy Systems Engineering, Technology Faculty, Fırat University, 23100 Elazig, Turkey
Abstract:Peak-details are often smoothed when deconvolution methods are used for spectral restoration. In order to preserve spectral details, detail-preserving regularization is devised and a semi-blind deconvolution method with the detail-preserving regularization (SBD-DP) is proposed. The cost function of SBD-DP is formulated and the numerical solution processes are deduced for restoring spectra and estimating parameter of blur kernel. The deconvolution results of simulated spectra demonstrate that the proposed SBD-DP can restore the spectrum effectively and has a merit on preserving peak details, as well as can estimate the parameter of blur kernel accurately. Then the deconvolution result of experimental Raman spectrum indicates the effectiveness of the proposed SBD-DP method on improving spectral resolution.
Keywords:Spectral restoration  Semi-blind deconvolution  Detail-preserving regularization  Raman spectrum
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