Motion detection through scattering media using speckle intensity correlation differences

Imaging and tracking objects hidden behind scattering media is challenging as multiple scattering randomizes the optical wavefront and produces seemingly random speckle patterns. While the optical memory effect enables the recovery of object information from speckle autocorrelations, many existing approaches rely on phase-retrieval algorithms, which are computationally expensive and unsuitable for dynamic scenes. In this work, we propose a numerical framework for motion detection through scattering media based on speckle intensity correlation analysis. Instead of reconstructing the object at each frame, motion is extracted from temporal differences in speckle intensity correlations, specifically I(t_n) ⋆ I(t₀)−I(t₀) ⋆ I(t₀), which suppresses the static background and isolates dynamic components. Motion detection is performed using correlation-based metrics and the structural similarity index (SSIM), combined with an adaptive exponentially weighted moving average (EWMA) thresholding scheme. Simulations incorporating memory-effect-induced blurring and additive Gaussian noise demonstrate robust detection of motion and object disappearance events without requiring phase retrieval. The proposed approach provides a computationally efficient alternative for motion detection in scattering environments.