Motion-enhanced resolution in dynamic single-pixel imaging

Single-pixel imaging uses a single-pixel detector and sequential structured illumination to reconstruct images, offering remarkable flexibility across spectral bands. A longstanding challenge is that object or platform motion during acquisition is traditionally regarded as a source of blurring and degradation. Here, we present a paradigm in which object motion is reinterpreted as a beneficial source of sub-pixel sampling diversity rather than a detriment. By accurately tracking translational motion-accomplished via geometric moment illumination patterns fused with Hadamard patterns-we encode the known motion into the SPI forward model as structured perturbations. This approach converts motion from a blurring nuisance into a valuable imaging resource, effectively increasing the sampling density beyond the native grid. Incorporating the motion information directly into the inverse problem, we demonstrate that an enhanced-resolved reconstruction of the scene becomes achievable. The resulting linear measurement system, solved via total variation minimization, yields finer image details than SPI reconstructions acquired with a stationary target. Our work suggests that motion in SPI, far from being merely something to mitigate, can be harnessed to fundamentally improve SPI resolution and fidelity in dynamic scenes.