A Novel Baseline Correction Algorithm

Abstract

This paper studies baseline correction algorithms for subtracting the background of real-word signal. A novel baseline correction algorithm is proposed that can be solved by random signal processing. With respect to generalized statistical features of the raw data, an appropriate threshold of standard deviation is set to extract the true baseline points unfailingly. Under the generalized meaning, the background at one signal point is substituted by the statistical features of its local window. By using this proposed algorithm, we established a time varying signal baseline independently and accurately. And performance evaluation shows that the proposed algorithm is more elaborate and tolerant of real-word data than the previous ones.