Analysis of Entropy-Based Denoising Algorithm's Performance on Signals in Colored Noise Environments

In this paper, the ability of local-entropy-based algorithm for extraction of useful information content of nonstationary signals embedded in colored noise environments is investigated. The local-entropy-based algorithm has been introduced in literature as an automatic method for signal denoising, however its application has so far been limited to white noise removal. The algorithm's effects on signals corrupted by pink (flicker) and blue noise, reported in this paper, are consistently beneficial for signals with different noise power spectra, proving the algorithm's ability to perform well in various environments. The algorithms's performance in pink and blue noise is shown on examples of dolphin's and bat's calls.