LAUSR

Abstract Baseline correction in time series of ground motion is a challenging problem in research pertaining to strong ground motion. In previous studies in this area, numerous methods have been proposed to identify baseline drift. However, there is no systematic approach to verify the proposed methods. In this paper, we propose a vision-based approach to evaluate baseline correction methods quantitatively. In addition, for our proposed baseline correction method based on L1-norm optimization, we analyze the method in detail and provide a thorough analysis of the method based on experimental data. From the comparison, our method shows good performance in recovering the baseline.