Dynamic speckle contrast and principal component analysis for infrasound frequency identification and clustering

¹ Department of Physics, M.S.P. Arts, Science & K.P.T. Commerce College Manora, Dist.-Washim, Maharashtra, India
² Department of Physics, Shri Shivaji Science and Arts College Chikhli, Dist. Buldana, Maharashtra, India
³ Department of Physics, Institute of Science Nagpur, Maharashtra, India

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 26 June 2026

Abstract

Monitoring acoustic signals is straightforward when the audio signals can be directly accessed. In scenarios where direct audio capture isn't feasible, converting sound into optical data offers a powerful alternative. Optical data can then be encoded into speckle images. These images can be processed using various statistical tools for correlating the temporally spaced images with audio signals. We present a simple method using two tools: Dynamical Speckle Contrast (DSC) and Principal Component Analysis (PCA). Using these tools, we have successfully matched the temporal variation of the infrasound signal with that of speckle contrast and have been able to cluster the frequencies present in the signal.