Computational multi-spectral video imaging

Abstract

Multi-spectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multi-spectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra, to compute the multi-spectral image. We experimentally demonstrated spectral resolution of 9.6nm within the visible band (430nm to 718nm). We further show that the spatial resolution is enhanced by over 30% compared to the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Furthermore, our camera is able to computationally trade-off spectral resolution against the field of view in software without any change in hardware as long as sufficient sensor pixels are utilized for information encoding. Since no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

References in corpus (5)

• Multiwavelength Achromatic Metasurfaces by Dispersive Phase Compensation
• High-resolution and broadband all-fiber spectrometers
• FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation
• Multiplexed phase-space imaging for 3D fluorescence microscopy
• Computational snapshot angular-spectral lensless imaging

Cited by in corpus (9)

• A broadband hyperspectral image sensor with high spatio-temporal resolution
• Deep Learning Enabled Real Time Speckle Recognition and Hyperspectral Imaging using a Multimode Fiber Array
• Imaging from the Visible to the Longwave Infrared wavelengths via an inverse-designed flat lens
• Inverse-designed flat lens for imaging in the visible & near-infrared with diameter > 3mm and NA=0.3
• Compressive Spectral Imaging with Diffractive Lenses
• Snapshot fiber spectral imaging using speckle correlations and compressive sensing
• High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
• Imaging over an unlimited bandwidth with a single diffractive surface
• Machine-learning enables Image Reconstruction and Classification in a "see-through" camera