title: Morphological weighted penalized least squares for background correction.
abstract: Backgrounds existing in the analytical signal always impair the effectiveness of signals and compromise selectivity and sensitivity of analytical methods. In order to perform further qualitative or quantitative analysis, the background should be corrected with a reasonable method. For this purpose, a new automatic method for background correction, which is based on morphological operations and weighted penalized least squares (MPLS), has been developed in this paper. It requires neither prior knowledge about the background nor an iteration procedure or manual selection of a suitable local minimum value. The method has been successfully applied to simulated datasets as well as experimental datasets from different instruments. The results show that the method is quite flexible and could handle different kinds of backgrounds. The proposed MPLS method is implemented and available as an open source package at http://code.google.com/p/mpls.
authors.affiliation: Yunnan Academy of Tobacco Science, Kunming 650106, PR China.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Li
authors.forename: De-Jian
authors.initials: DJ
authors.lastname: Zhan
authors.forename: Jia-Jun
authors.initials: JJ
authors.lastname: Wang
authors.forename: Jing
authors.initials: J
authors.lastname: Huang
authors.forename: Qing-Song
authors.initials: QS
authors.lastname: Xu
authors.forename: Zhi-Min
authors.initials: ZM
authors.lastname: Zhang
authors.forename: Yi-Bao
authors.initials: YB
authors.lastname: Zheng
authors.forename: Yi-Zeng
authors.initials: YZ
authors.lastname: Liang
authors.forename: Hong
authors.initials: H
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D016018:Least-Squares Analysis; D012906:Smoke / Q000032:analysis; D013059:Spectrum Analysis, Raman / Q000379:methods*; D014026:Nicotiana / Q000737:chemistry
chemical_list: D012906:Smoke