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Multiresolution method | Laboratory of Mathematical Methods of Image Processing

Multiresolution method

res_audionoise.png

Alexey Lukin

Filter banks with fixed time-frequency resolution, such as the Short-Time Fourier Transform (STFT), are a common tool for many audio analysis and processing applications allowing effective implementation via the Fast Fourier Transform (FFT). The fixed time-frequency resolution of the STFT can lead to the undesirable smearing of events in both time and frequency. We suggest adaptively varying STFT time-frequency resolution in order to reduce filter bank-specific artifacts while retaining adequate frequency resolution. Several strategies for systematic adaptation of time-frequency resolution are proposed. The introduced approach is demonstrated as applied to spectrogram displays, noise reduction, and spectral effects processing.

 

Teaching

Lecture slides on multiresolution method (Power Point) discussing spectral analysis and processing with a multiresolution STFT.

 

Publications

  • M.S.Tkachenko, A.S.Lukin "A multiresolution spectral subtraction algorithm for noise suppression in audio signals" // Proceedings of 12-th International Conference and Exhibition "Digital Signal Processing and its Applications" (DSPA'2010), vol. 1, p. 226. Abstract: PDF, 44 Kb, full text in Russian: PDF, 131 Kb
  • A.Lukin, J.Todd "Adaptive Time-Frequency Resolution for Analysis and Processing of Audio" // 120th Audio Engineering Society Convention, Paris, France, May 2006, paper #6717. PDF, 555 Kb
  • A.Lukin "A Multiresolution Approach for Improving Quality of Image Denoising Algorithms" // IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2006), Toulouse, France, May 2006. PDF, 355 Kb
  • A.Lukin, D.Kalinkina, D.Kubasov "Adaptive Multiresolution Filter Banks for Image and Audio Processing" // Proceedings of GraphiCon'2005, Novosibirsk Akademgorodok, Russia, 2005, pp. 312-315. PDF, 205 Kb