Wavelet-based background and noise subtraction for fluorescence microscopy images

• DOI: 10.1364/boe.413181
• Publication Date: 2021-01-15T17:00:10Z
• Authors: Manuel Hüpfel; Andrei Yu. Kobitski; Weichun Zhang; G. Ulrich Nienhaus
• Keywords: Ground truth

Fluorescence microscopy images are inevitably contaminated by background intensity contributions. from out-of-focus planes and scattered light important sources of slowly varying, low spatial frequency background, whereas varying pixel to (high noise) is introduced the detection system. Here we present a powerful, easy-to-use software, wavelet-based noise subtraction (WBNS), which effectively removes both these components. To assess its performance, apply WBNS synthetic compare results quantitatively with ground truth processed other removal algorithms. We further evaluate on real taken light-sheet microscope super-resolution stimulated emission depletion microscope. For cases, algorithm hardware-based techniques quantitative assessment results. shows an excellent performance in all applications significantly enhances visual appearance fluorescence images. Moreover, it may serve as pre-processing step for analysis.