High-Order Statistical Blind Deconvolution of Spectroscopic Data with a Gauss–Newton Algorithm

Authors: Yuan, Jinghe; Hu, Ziqiang

Source: Applied Spectroscopy, Volume 60, Issue 6, Pages 154A-168A and 573-712 (June 2006) , pp. 692-697(6)

Publisher: Society for Applied Spectroscopy

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Abstract:

The spectroscopic data recorded by a dispersion spectrophotometer are usually degraded by the response function of the instrument. To improve the resolving power, double or triple cascade spectrophotometers and narrow slits have been employed, but the total flux of the radiation available decreases accordingly, resulting in a lower signal-to-noise ratio (SNR) and a longer measurement time. However, the spectral resolution can be improved by mathematically removing the effect of the instrument response function. A high-order statistical Gauss–Newton algorithm is proposed to blindly deconvolve the measured spectroscopic data. The true spectrum and the instrument response function are estimated simultaneously. Experiments on artificial and real measured spectroscopic data demonstrate the feasibility of this method.

Keywords: BLIND DECONVOLUTION; GAUSS-NEWTON ALGORITHM; HIGH-ORDER; SPECTROSCOPIC DATA; STATISTICS

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/000370206777670648

Affiliations: Institute of Science and Technology for Opto-electron Information, Yantai University, Yantai 264005, China

Publication date: June 1, 2006

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