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Broadband Wide Field of View Imaging with Computational Mirrors

arXiv 2605.00029 ↗First posted 22 Apr 2026eess.IV cs.CV physics.opticscited by 0

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Abstract (arXiv)

Traditional glass-based optics are typically optimized for narrow 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 this entire range simultaneously. Mirrors represent a promising achromatic alternative; however, they are often sidelined by field curvature, and off-axis aberrations. This paper introduces Computational Mirrors, a framework that enables high-resolution, wide-field-of-view imaging across the complete VIS-SWIR spectrum using a single sensor. Our method is built on the observation that distinct regions of the field of view reach focus at varying distances from the mirror. By capturing a minimal focal stack (2-4 images), we utilize a computational backend to recover a sharp, all-in-focus image. A key contribution of this work is SeidelConv, a novel, physics-inspired, spatially-varying point spread function (PSF) model designed to accurately characterize and correct the off-axis aberrations inherent in simple concave mirrors. We demonstrate the efficacy of our approach using a first-of-its-kind 50mm F/1 optical system equipped with a VIS-SWIR sensor. Our system produces sharp images across RGB, NIR, and SWIR wavelengths without requiring refocusing, revealing material details invisible within individual spectral bands. We further validate the scalability of our approach with a 100mm F/2 system optimized for long-range imaging.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 30 references that are in the map. First posted on arXiv 22 Apr 2026.

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References · 8

  1. 2015Spatial Transformer Networkscited by 1,423
  2. 2017Deep Image Priorcited by 1,097
  3. 2020Plug-and-Play Image Restoration with Deep Denoiser Priorcited by 467
  4. 2023WIRE: Wavelet Implicit Neural Representationscited by 220
  5. 2020Simulating Anisoplanatic Turbulence by Sampling Inter-modal and Spatially Correlated Zernike Coefficientscited by 27
  6. 2023Learning Lens Blur Fieldscited by 6
  7. 2022Ring deconvolution microscopy: exploiting symmetry for efficient spatially varying aberration correctioncited by 3
  8. 2024CoordGate: Efficiently Computing Spatially-Varying Convolutions in Convolutional Neural Networkscited by 2

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