Related papers: Integrated Snapshot Near-infrared Hypersepctral Im…
Here, we present an astrophotonic spectrograph in the near-IR H-band (1.45 -1.65 $\mu m$) and a spectral resolution ($\lambda/\delta\lambda$) of 1500. The main dispersing element of the spectrograph is a photonic chip based on…
Optical super-oscillation enables far-field super-resolution imaging beyond diffraction limits. However, the existing super-oscillatory lens for the spatial super-resolution imaging system still confronts critical limitations in performance…
We present a new and innovative near-infrared multi-band ultraprecise spectroimager (NIMBUS) for SOFIA. This design is capable of characterizing a large sample of extrasolar planet atmospheres by measuring elemental and molecular abundances…
We present the architectural concept for the Far-Infrared Enhanced Survey Spectrometer (FIRESS) for the Probe Mission for far-IR Astrophysics (PRIMA). FIRESS spans the 24--235 micron range with four R ~ 100 slit-fed grating modules, each…
Spectral imaging enables spatially-resolved identification of materials in remote sensing, biomedicine, and astronomy. However, acquisition times require balancing spectral and spatial resolution with signal-to-noise. Hyperspectral imaging…
Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems. However, only high-resolution multispectral (HrMS) and low-resolution hyperspectral (LrHS) images can…
In this paper, we propose a novel image denoising algorithm exploiting features from both spatial as well as transformed domain. We implement intensity-invariance based improved grouping for collaborative support-agnostic sparse…
To achieve its ambitious scientific goals, the Near-Infrared Spectrograph, NIRSpec, on board the Webb Space Telescope, needs to meet very demanding throughput requirements, here quantified in terms of photon-conversion efficiency (PCE).…
Classic designs of hyperspectral instrumentation densely sample the spatial and spectral information of the scene of interest. Data may be compressed after the acquisition. In this paper we introduce a framework for the design of an…
Recent denoising algorithms based on the "blind-spot" strategy show impressive blind image denoising performances, without utilizing any external dataset. While the methods excel in recovering highly contaminated images, we observe that…
This study proposes an algorithm based on a notch filter camera array system for simultaneous super-resolution imaging and spectral reconstruction, enhancing the spatial resolution and multispectral imaging capabilities of targets. In this…
We present integrated optical spectrophotometry for a sample of 417 nearby galaxies. Our observations consist of spatially integrated, S/N=10-100 spectroscopy between 3600 and 6900 Angstroms at ~8 Angstroms FWHM resolution. In addition, we…
WINERED is a newly built high-efficiency (throughput$ > 25-30\%$) and high-resolution spectrograph customized for short NIR bands at 0.9-1.35 ${\rm \mu}$m. WINERED is equipped with ambient temperature optics and a cryogenic camera using a…
Hyperspectral compressive imaging takes advantage of compressive sensing theory to achieve coded aperture snapshot measurement without temporal scanning, and the entire three-dimensional spatial-spectral data is captured by a…
We present a Ge-on_Si CMOS image sensor with backside illumination for the near-infrared electromagnetic waves, wavelengths range 300-1700nm, detection essential for optical sensor technology. The micro-holes help to enhance the optical…
Compound eyes found in insects provide intriguing sources of biological inspiration for miniaturized imaging systems. Inspired by such insect eye structures, we demonstrate an ultrathin arrayed camera enabled by a flat multilevel…
Spectral imaging in the mid-infrared (MIR) range provides simultaneous morphological and chemical information of a wide variety of samples. However, current MIR technologies struggle to produce high-definition images over a broad spectral…
Hyperspectral images are typically composed of hundreds of narrow and contiguous spectral bands, each containing information regarding the material composition of the imaged scene. However, these images can be affected by various sources of…
In this paper we propose a convolutional neural network that is designed to upsample a series of sparse range measurements based on the contextual cues gleaned from a high resolution intensity image. Our approach draws inspiration from…
We present a fast and accurate method for dense depth reconstruction from sparsely sampled light fields obtained using a synchronized camera array. In our method, the source images are over-segmented into non-overlapping compact superpixels…