The application of adaptive step threshold method in fluorescence signal detection

The microfluidic fluorescence detection system's strengths are high sensitivity and easy operability, nevertheless it may also be more vulnerable to electronic circuit, ambient light, quenching effect which can influence the quality of the signal detection by adding noise. In order to improve the efficiency of the fluorescence detection system, eliminating noises from the signal is a significant step. In this paper, an adaptive step thresholding (Adaptive Step Thresholding, AST) denoising method based on wavelet analysis is proposed. According to the features of the fluorescent protein signal, noise is spread over a high frequency band of signal. The new methods is applied to the high-frequency components obtained by wavelet decomposing the signal and update threshold adaptively. The experimental results show that the AST sloves the weakness of the constant deviation by traditional wavelet threshold denoising and increases the Signal - to - Noise Ratio(SNR) of the denoising fluorescent protein signal, it provides a practical application value for the weak signal denoising.