Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13275
Title: Spectrogram denoising for the automated extraction of dolphin whistle contours
Authors: ASITHA MALLAWAARACHCHI
Keywords: Spectrogram, Image denoising, dolphin vocalisation
Issue Date: 1-Jun-2008
Source: ASITHA MALLAWAARACHCHI (2008-06-01). Spectrogram denoising for the automated extraction of dolphin whistle contours. ScholarBank@NUS Repository.
Abstract: Marine mammal vocalizations are often analyzed using time-frequency representations (TFRs) which highlight their non-stationarities. One commonly used TFR is the spectrogram. The characteristic spectrogram time-frequency (TF) contours of marine mammal vocalizations play a significant role in whistle classification and individual or group identification. A major hurdle in the robust automated extraction of TF contours from spectrograms is underwater noise. An image-based algorithm has been developed for de-noising and extraction of TF contours from noisy underwater recordings. An objective procedure for measuring the accuracy of extracted spectrogram contours is also proposed. This method is shown to perform well when dealing with the challenging problem of de-noising broadband transients commonly encountered in warm shallow waters inhabited by snapping shrimp. Furthermore, we believe it would also be useful with other types of broadband transient noise.
URI: http://scholarbank.nus.edu.sg/handle/10635/13275
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