Spatial-spectral resolution tunable snapshot imaging spectrometer: analytical design and implementation

Deep Learning Empowered Parallelized Metasurface Computed Tomography Snapshot Spectral Imaging

Snapshot spectral imaging is an emerging technology for fast data acquisition in dynamic environments, capturing high-volume spatial-spectral information in a single snapshot. However, it suffers from bulky cascading optics and cannot be directly used in space-restricted scenarios such as endoscope-assisted brain microsurgery and real-time cellular tissue imaging. In this work, an ultracompact strategy of parallelized metasurface computed tomography empowered by generative deep learning is proposed, which can effectively reduce the optics volume in snapshot spectral imaging from cm3 scale to sub-mm3 scale while retaining high resolution and speed of imaging so that the above-mentioned pain point problem is well addressed. The system comprises seven multifunctional sub-metasurfaces simultaneously acquiring multi-angle spectral projection and integration information of the target, uses the system-calibrated point spread functions as wavelength and spatial position distributions, and incorporates a generative adversarial deep neural network for fast reconstruction of spatial-spectral multiplexed images. Experimental results show that single snapshot imaging can be achieved in 38 ms with a spectral resolution of 10 nm in the spectral range of 450-650 nm. This technique paves the way for snapshot spectral imaging integration into various highly miniaturized microscopy and endoscopic imaging systems in applications such as advanced medical diagnosis.

Trends in Snapshot Spectral Imaging: Systems, Processing, and Quality

Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the expense of the spatio-spectral resolution, allowing for the observation of temporal events. Designing, realising, and deploying such technologies is yet challenging, particularly due to the lack of clear, user-meaningful quality criteria across diverse applications, sensor types, and workflows. Key research gaps include optimising raw image processing from snapshot spectral imagers and assessing spectral image and video quality in ways valuable to end-users, manufacturers, and developers. This paper identifies several challenges and current opportunities. It proposes considering them jointly and suggests creating a new unified snapshot spectral imaging paradigm that would combine new systems and standards, new algorithms, new cost functions, and quality indices.

Optical design and fabrication of a multi-channel imaging spectrometer for combustion flame monitoring

We design and construct a broadband integrated multi-channel imaging spectrometer (MCIS) from visible light to near-infrared. This system can directly obtain spectral images that conform to the consistent visual habits of the human eyes through a single exposure of the detector. The genetic algorithm is used to calculate system parameters to minimize pixel waste between spectral channels, achieving nearly 100% utilization of detector pixels. The field stop suppresses stray light in the system. This device is used for imaging an optical-resolution target, an object, and a furnace to verify the basic principles of the system. The results indicate that the system can effectively utilize detectors to monitor high-temperature objects in the visible to near-infrared wavelength range.

Snapshot spectral imaging: from spatial-spectral mapping to metasurface-based imaging

Snapshot spectral imaging technology enables the capture of complete spectral information of objects in an extremely short period of time, offering wide-ranging applications in fields requiring dynamic observations such as environmental monitoring, medical diagnostics, and industrial inspection. In the past decades, snapshot spectral imaging has made remarkable breakthroughs with the emergence of new computational theories and optical components. From the early days of using various spatial-spectral data mapping methods, they have evolved to later attempts to encode various dimensions of light, such as amplitude, phase, and wavelength, and then computationally reconstruct them. This review focuses on a systematic presentation of the system architecture and mathematical modeling of these snapshot spectral imaging techniques. In addition, the introduction of metasurfaces expands the modulation of spatial-spectral data and brings advantages such as system size reduction, which has become a research hotspot in recent years and is regarded as the key to the next-generation snapshot spectral imaging techniques. This paper provides a systematic overview of the applications of metasurfaces in snapshot spectral imaging and provides an outlook on future directions and research priorities.

Compact freeform-surface-based Offner imaging spectrometer with both a long-slit and broadband

Current imaging spectrometers with conventional optical elements face major challenges in achieving a large field of view (FOV), broadband and compact structure simultaneously. In this paper, a compact freeform-surface-based Offner imaging spectrometer with both a long-slit and a broadband (CISLS) is proposed. To keep a long slit and an anastigmatic imaging, the slit off-axis amount of the initial system is within a specific range theoretically. While to achieve a compact structure, the slit off-axis amount should be away from the specific range and as small as possible. Based on the vector aberration theory and the analytical study, Zernike polynomial terms Z5 and Z6 introduce the astigmatism independent of FOV. They are utilized to well balance the astigmatism when the slit off-axis amount is away from the specific range, helping a miniaturization of the system. Other Zernike polynomial terms below the eighth order introduce the astigmatism related to FOV. They contribute to balancing the astigmatism that produced with the increasing of the FOV, thus achieving a wide FOV. The design results show that the proposed CISLS with a high spectral resolution of 2.7 nm achieves a long slit of 30 mm in length but a small size of only 60 mm × 64 mm × 90 mm in volume under a broadband from 400 nm to 1000 nm.

Compact multi-spectral-resolution Wynne-Offner imaging spectrometer with a long slit

Current imaging spectrometers are developed towards a large field of view (FOV) as well as high resolution to obtain more spatial and spectral information. However, imaging spectrometers with a large FOV and high resolution produce a huge image data cube, which increases the difficulty of spectral data acquisition and processing. In practical applications, it is more reasonable and helpful to identify different targets within a large FOV with different spectral resolutions. In this paper, a compact multi-spectral-resolution Wynne-Offner imaging spectrometer with a long slit is proposed by introducing a special diffraction grating with multi-groove densities at different areas. With the increasing of the groove density and the slit length, the astigmatism of the Wynne-Offner imaging spectrometer increases sharply. Therefore, the relationships between the astigmatism and both the groove density and slit length are studied. Moreover, a holographic grating is introduced. The holographic aberrations produced are utilized to balance the residual astigmatism of the imaging spectrometer. The design results show that the system is only 60m m×115m m×103m m in volume but achieves both a long slit of 20 mm in length and a waveband from 400 nm to 760 nm with three kinds of spectral resolutions of 2 nm, 1 nm, and 0.5 nm. The designed compact multi-spectral-resolution Wynne-Offner imaging spectrometer can be widely applied in the fields of crop classification and pest detection, which require both a large FOV and multiple spectral resolutions.

A Customisable Data Acquisition System for Open-Source Hyperspectral Imaging

Hyperspectral imagers, or imaging spectrometers, are used in many remote sensing environmental studies in fields such as agriculture, forestry, geology, and hydrology. In recent years, compact hyperspectral imagers were developed using commercial-off-the-shelf components, but there are not yet any off-the-shelf data acquisition systems on the market to deploy them. The lack of a self-contained data acquisition system with navigation sensors is a challenge that needs to be overcome to successfully deploy these sensors on remote platforms such as drones and aircraft. Our work is the first successful attempt to deploy an entirely open-source system that is able to collect hyperspectral and navigation data concurrently for direct georeferencing. In this paper, we describe a low-cost, lightweight, and deployable data acquisition device for the open-source hyperspectral imager (OpenHSI). We utilised commercial-off-the-shelf hardware and open-source software to create a compact data acquisition device that can be easily transported and deployed. The device includes a microcontroller and a custom-designed PCB board to interface with ancillary sensors and a Raspberry Pi 4B/NVIDIA Jetson. We demonstrated our data acquisition system on a Matrice M600 drone at a beach in Sydney, Australia, collecting timestamped hyperspectral, navigation, and orientation data in parallel. Using the navigation and orientation data, the hyperspectral data were georeferenced. While the entire system including the pushbroom hyperspectral imager and housing weighed 735 g, it was designed to be easy to assemble and modify. This low-cost, customisable, deployable data acquisition system provides a cost-effective solution for the remote sensing of hyperspectral data for everyone.

Ultra-compact dual band imaging spectrometer with freeform prisms

Wide spectrum and miniaturization are the main challenges in the imaging spectrometer design. In this paper, we propose an ultra-compact dual band imaging spectrometer (CDBIS) with cemented freeform prisms, which works at both the visible-near-infrared (VNIR) from 400 nm to 1000 nm and the shortwave-infrared (SWIR) from 1000 nm to 1700 nm. The imaging spectrometer is only composed of three cemented prisms, a primary prism and two triangular prisms. And a freeform surface characterized by the Zernike polynomial is introduced in each prism. The CDBIS is dispersed by a diffraction grating, which is designed on the second surface of the primary prism. Based on vector aberration theory (VAT), the relationship among the astigmatism generated by the introduced freeform surfaces, the wavelength, and the field of view is studied. Accordingly, a wideband is realized by introducing the freeform surfaces after the diffraction grating. Furthermore, through optimizing the coefficients of Zernike polynomial terms, residual astigmatism at different wavelengths is well balanced. An imaging spectrometer with a volume of only 100c m 3 is obtained, with a spectral resolution of 1.45 nm at VNIR and 2.40 nm at SWIR, respectively. It has a huge potential for broadband space exploration.

Dual-channel snapshot imaging spectrometer with wide spectrum and high resolution

The comprehensive analysis of dynamic targets brings about the demand for capturing spatial and spectral dimensions of visual information instantaneously, which leads to the emergence of snapshot spectral imaging technologies. While current snapshot systems face major challenges in the development of wide working band range as well as high resolution, our novel dual-channel snapshot imaging spectrometer (DSIS), to the best of our knowlledge, demonstrates the capability to achieve both wide spectrum and high resolution in a compact structure. By dint of the interaction between the working band range and field of view (FOV), reasonable limits on FOV are set to avoid spectral overlap. Further, we develop a dual-channel imaging method specifically for DSIS to separate the whole spectral range into two parts, alleviating the spectral overlap on each image surface, improving the tolerance of the system for a wider working band range, and breaking through structural constraints. In addition, an optimal FOV perpendicular to the dispersion direction is determined by the trade-off between FOV and astigmatism. DSIS enables the acquisition of 53×11 spatial elements with up to 250 spectral channels in a wide spectrum from 400 to 795 nm. The theoretical study and optimal design of DSIS are further evaluated through the simulation experiments of spectral imaging.