Virtual Mode Sorting: A Hardware-Free Path to Super-Resolution Imaging Across Wavelengths

The diffraction limit is often treated as a hard barrier in imaging, but in reality a surprising amount of high-frequency information is still present in a blurred image, it’s just not directly accessible. Many groups have tried to recover this hidden structure using specialized optics or interferometry, but these approaches require careful alignment and are not practical outside controlled lab settings. In this work, we show that it is possible to go beyond the diffraction limit using only standard intensity images from an ordinary camera. Our method, which we call virtual mode sorting, analyzes images by projecting them onto a set of spatial modes that preserve fine structure normally lost to blur. This allows us to recover sub-diffraction information in a stable and physically meaningful way, without deconvolution or learned priors. We demonstrate a significant resolution improvement in both optical and acoustic imaging experiments, showing that the approach is wavelength-independent and works for incoherent systems as well. The method has a built-in parameter that lets the user balance resolution gain against noise sensitivity, and it remains robust in low signal-to-noise conditions, especially when paired with simple denoising. The key advantage is practicality: there is no need for calibrated hardware, wavefront control, or interferometry. Virtual mode sorting can be used as a drop-in upgrade for existing microscopes, ultrasound systems, or remote imaging platforms, making super-resolution achievable in real-world settings rather than just idealized experiments.