Computational Speckle Pattern Interferometry

Visually imperceptible surface deformations encode rich information---from the mechanical properties of an object to the acoustic vibrations present in the surrounding environment. Existing optical techniques reveal these subtle motions by employing coherent illumination and capturing multiple measurements over time. In this paper, we introduce Computational Speckle Pattern Interferometry (CSPI), a novel single-shot approach that estimates per-pixel displacement and motion by leveraging a phasor-based image formation model and an optical-flow-inspired reconstruction algorithm. Our key insight is that the image formation process can be factorized to jointly recover spatial coefficients and temporal dynamics. Unlike traditional interferometric methods, CSPI requires no precision instrumentation to perform phase stepping. We demonstrate its effectiveness by measuring per-pixel displacements and motions at sub-micrometer scales, visualizing high-frequency vibrations of a tuning fork and a Chladni plate, and recovering sound indirectly from these vibrations.