Implementation of the Detector Precision Characteristics Based Wavelet Denoising Algorithm
This page contains an implementation of the adaptive wavelet denoising algorithm for fluorescence microscopy images based on detector precision characteristics, described in: T. Bernas, R. Starosolski, R. Wójcicki: Application of detector precision characteristics for the denoising of biological micrographs in the wavelet domain, Biomedical Signal Processing and Control, 2015, Vol. 19, pp. 1-13,
This software is intended for research purposes only; it is provided "as is"; author makes no warranty of any kind, either express or implied, with respect to this software. This work was supported by NCN (Polish National Science Centre) grants 2013/09/B/NZ3/01389 and 2012/05/E/ST2/02180 and by POIG.02.03.01-24-099/13 grant: GeCONiI-Upper Silesian Center for Computational Science and Engineering.
The implementation by Tytus Bernas (model_den.m - MATLAB denoising function and cheb_fit_coeff.mat - coefficients of wavelet noise model) is contained in this archive (zip).
You may also like to check out the tools for microscopy image compression exploiting detector precision characteristics or just for image transformations.

Roman Starosolski