Full band denoising of room impulse response in the wavelet domain with dictionary learning
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2026-04-30 v1 Optimization and Control
Abstract
Conventional wavelet-domain methods for room impulse response denoising rely on thresholding detail coefficients, which is unsuited for low frequencies. In this work, we introduce a wavelet-based post-processing algorithm that extends denoising to approximation coefficients by means of sparse dictionary learning with a time-varying error tolerance. The proposed method leverages an exponential decay envelope model to adapt reconstruction accuracy according to the local signal-to-noise ratio. This approach significantly improves low-frequency denoising of synthetic and measured room impulse responses compared to the baseline method, leading to more accurate estimation of acoustic parameters such as decay time.
Keywords
Cite
@article{arxiv.2604.26669,
title = {Full band denoising of room impulse response in the wavelet domain with dictionary learning},
author = {Théophile Dupré and Romain Couderc and Miguel Moleron and Axel Coulon and Rémy Bruno and Arnaud Laborie},
journal= {arXiv preprint arXiv:2604.26669},
year = {2026}
}