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- W2276266075 abstract "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 obtain a better performance than state-of-the-art methods, and to obtain satisfying deconvolution results with fewer artifacts. The recovered infrared spectra can easily extract the spectral features and recognize unknown objects." @default.
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- W2276266075 date "2015-10-16" @default.
- W2276266075 modified "2023-09-27" @default.
- W2276266075 title "Blind deconvolution using the similarity of multiscales regularization for infrared spectrum" @default.
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- W2276266075 doi "https://doi.org/10.1088/0957-0233/26/11/115502" @default.
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