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Register a new userSingle-shot multispectral imaging with a monochromatic camera
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Multispectral imaging plays an important role in many applications from astronomical imaging, earth observation to biomedical imaging. However, the current technologies are complex with multiple alignment-sensitive components, predetermined spatial and spectral parameters by manufactures. Here, we demonstrate a single-shot multispectral imaging technique that gives flexibility to end-users with a very simple optical setup, thank to spatial correlation and spectral decorrelation of speckle patterns. These seemingly random speckle patterns are point spreading functions (PSFs) generated by light from point sources propagating through a strongly scattering medium. The spatial correlation of PSFs allows image recovery with deconvolution techniques, while the spectral decorrelation allows them to play the role of tune-able spectral filters in the deconvolution process. Our demonstrations utilizing optical physics of strongly scattering media and computational imaging present the most cost-effective approach for multispectral imaging with great advantages.
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A multispectral image camera captures image data within specific wavelength ranges in narrow wavelength bands across the electromagnetic spectrum. Images from a multispectral camera can extract additional information that the human eye or a normal camera fails to capture and thus may have important applications in precision agriculture, forestry, medicine and object identification. Conventional multispectral cameras are made up of multiple image sensors each fitted with a narrow passband wavelength filter and optics, which makes them heavy, bulky, power hungry and very expensive. The multiple optics also create image co-registration problem. Here, we demonstrate a single sensor based three band multispectral camera using a narrow spectral band RGB colour mosaic in a Bayer pattern integrated on a monochrome CMOS sensor. The narrow band colour mosaic is made of a hybrid combination of plasmonic colour filters and heterostructured dielectric multilayer. The demonstrated camera technology has reduced cost, weight, size and power by almost n times (where n is the number of bands) compared to a conventional multispectral camera.
Fluorescence imaging is indispensable to biology and neuroscience. The need for large-scale imaging in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes / miniscopes are inherently constrained by their limited space-bandwidth-product, shallow depth-of-field, and the inability to resolve 3D distributed emitters. Here, we present a Computational Miniature Mesoscope (CM$^2$) that overcomes these bottlenecks and enables single-shot 3D imaging across an 8 $times$ 7-mm$^2$ field-of-view and 2.5-mm depth-of-field, achieving 7-$mu$m lateral resolution and better than 200-$mu$m axial resolution. Notably, the CM$^2$ has a compact lightweight design that integrates a microlens array for imaging and an LED array for excitation in a single platform. Its expanded imaging capability is enabled by computational imaging that augments the optics by algorithms. We experimentally validate the mesoscopic 3D imaging capability on volumetrically distributed fluorescent beads and fibers. We further quantify the effects of bulk scattering and background fluorescence on phantom experiments.
A spectral camera based on ghost imaging via sparsity constraints (GISC) acquires a spectral data-cube (x; y; {lambda}) through a single exposure. The noise immunity of the system is one of the important factors affecting the quality of the reconstructed images, especially at low sampling rates. Tailoring the intensity to generate super-Rayleigh speckle patterns which have superior noise immunity may offer an effective route to promote the imaging quality of GISC spectral camera. According to the structure of GISC spectral camera, we proposed a universal method for generating super-Rayleigh speckle patterns with customized intensity statistics based on the principle of reversibility of light. Simulation and experimental results demonstrate that, within a wide imaging spectral bandwidth, GISC spectral camera with super-Rayleigh modulator not only has superior noise immunity, but also has higher imaging quality at low sampling rates. This work will promote the application of GISC spectral camera by improving the quality of imaging results, especially in weak-light illumination.
One-shot spectral imaging that can obtain spectral information from different points in space at one time has always been difficult to achieve, and is extremely important for both fundamental scientific research and various practical applications. In this study, one-shot ultraspectral imaging by fitting thousands of micro-spectrometers on a chip, is proposed and demonstrated. Exotic light modulation is achieved by using a reconfigurable metasurface supercell, which enables 155,216 image-adaptive micro-spectrometers, simultaneously guaranteeing the spectral-pixel density and reconstructed spectral quality. By constructing a compressive-sensing algorithm, the device can reconstruct ultraspectral imaging ($Deltalambda$/$lambda$~0.001) covering a 300-nm-wide visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm standard deviation and spectral resolution of 0.8 nm. This scheme can be extended to almost any commercial camera with different spectral bands to seamlessly switch between image and spectral image, and opens up a new space for the application of spectral analysis combining with image recognition and intellisense.
Based on point spread function (PSF) engineering and astigmatism due to a pair of cylindrical lenses, a novel compressed imaging mechanism is proposed to achieve single-shot incoherent 3D imaging. The speckle-like PSF of the imaging system is sensitive to axial shift, which makes it feasible to reconstruct a 3D image by solving an optimization problem with sparsity constraint. With the experimentally calibrated PSFs, the proposed method is demonstrated by a synthetic 3D point object and real 3D object, and the images in different axial slices can be reconstructed faithfully. Moreover, 3D multispectral compressed imaging is explored with the same system, and the result is rather satisfactory with a synthetic point object. Because of the inherent compatibility between the compression in spectral and axial dimensions, the proposed mechanism has the potential to be a unified framework for multi-dimensional compressed imaging.
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