光谱信号区域基线拟合算法

Baseline Fitting Algorithm of Spectral Signal Region

为消除基线畸变对光谱信号后续处理产生的不利影响,提出了一种光谱信号区域基线拟合算法.首先,利用渐变惯性力和吸引力的思想,针对具有曲率突变的基线提出了GradSuck拟合算法,该算法弥补了多项式拟合算法在信号区域周围基线曲率发生突变时拟合基线不准确的不足;然后将这种算法与分段二次多项式拟合算法进行结合,提出了更具有普适性的信号区域基线拟合算法,同时将该算法与不同的基线拟合算法做了对比.实验结果表明,信号区域基线拟合算法在不同的基线类型和不同的信噪比下均具有较高的准确性和稳定性,其总体拟合精度的相对误差仅为分段二次多项式拟合的47.0%,为AirPLS拟合的35.6%,为Wavelet拟合的20%,且由于只对光谱信号区域进行基线拟合,因此具有较好的实时性.

A baseline fitting algorithm for spectral signal region is proposed in order to eliminate the adverse effects of baseline distortion in spectral processing.First,a GradSuck fitting algorithm is proposed for baseline with abrupt curvature by using the idea of gradient inertia force and suction,which cover the shortage of the piecewise quadratic polynomial fitting algorithm when the baseline curvature around the signal area changes suddenly.Then this algorithm is combined with the piecewise quadratic polynomial fitting algorithm to propose a more general fitting algorithm for spectral signal region.At the same time,the proposed algorithm has been compared with different baselines fitting algorithms.Experiments under various baseline types with different SNR show that the baseline fitting algorithm of signal region has reliable accuracy and stability,and it can extract the spectral baseline better than other algorithms.The relative error of its whole fitting accuracy is only 47.0%of the quadratic polynomial fitting,35.6%of the AirPLS fitting,and 20%of the wavelet fitting.And it also has high real-time performance because of only fitting the baseline of the signal region.