Broadband Wide Field of View Imaging with Computational Mirrors

Traditional glass-based optics are typically optimized for nar-row spectral bands, such as the visible (400–700nm) or shortwave infrared(1000–1800nm). While the emergence of VIS-SWIR sensors (400–1700nm)offers transformative potential, refractive optics struggle to focus thisentire range simultaneously. Mirrors represent a promising achromaticalternative; however, they are often sidelined by field curvature, and off-axis aberrations. This paper introduces Computational Mirrors, aframework that enables high-resolution, full-field-of-view imaging acrossthe complete VIS-SWIR spectrum using a single sensor. Our method isbuilt on the observation that distinct regions of the field of view reachfocus at varying distances from the mirror. By capturing a minimal fo-cal stack (2–4 images), we utilize a computational backend to recovera sharp, all-in-focus image. A key contribution of this paper is Seidel-Conv, a novel, physics-inspired, spatially-varying point spread function(PSF) model designed to accurately characterize and correct the off-axisaberrations inherent in simple concave mirrors. We demonstrate the ef-ficacy of our approach using a first-of-its-kind 50mm F/1 optical systemequipped with a VIS-SWIR sensor. Our system produces sharp imagesacross RGB, NIR, and SWIR wavelengths without requiring refocusing,revealing material details invisible within individual spectral bands. Wefurther validate the scalability of our approach with a 100mm F/2 systemoptimized for long-range imaging.