Repairing distorted hologram data for sound field reconstruction

Abstract

This paper proposes a distorted hologram data repair approach for sound field reconstruction. In this approach, an equivalent source model is established by placing a set of equivalent sources near the hologram surface to represent the measured hologram pressures. Each hologram pressure is simultaneously assigned an indicator to describe whether its measurement is corrupted by errors or not. This model is then formulated within a modal framework by utilizing the modes generated through the singular value decomposition of the transfer matrix between the hologram and nearby equivalent source surfaces. Subsequently, the indicators and modal coefficients are assigned the 0–1 and Gaussian prior distributions, respectively, and their posterior distributions are derived using the Bayesian method. The means of the posterior distributions are calculated to discriminate corrupted measurements and repair distorted hologram pressures. Repaired hologram pressures are finally utilized for reconstructions using the equivalent source method. Results from both numerical simulations conducted under various parameter settings and two experiments demonstrate the effectiveness of the proposed approach in automatically discriminating all the corrupted measurements and accurately repairing the distorted hologram pressures. Furthermore, the accuracy of the reconstructions using the repaired hologram pressures is comparable to that achieved with the correctly measured pressures.