Compressive Photon-Sieve Spectral Imaging

We develop a new compressive spectral imaging modality that utilizes a coded aperture and a photon-sieve for dispersion. The 3D spectral data cube is successfully reconstructed with as little as two shots using sparse recover

Comparison of ICON O+ density profiles with electron density profiles provided by COSMIC-2 and ground-based ionosondes

In October 2019, NASA-ICON was launched to observe the low-latitude ionosphere using in-situ and remote sensing instruments, from a LEO circular orbit at about 575 km altitude. The six satellites of the radio-occultation program COSMIC-2 were also successfully launched and currently provide up to 3000 electron density profiles on a daily basis since October 1, 2019. Besides, the network of ground-based ionosondes is constantly growing and allows retrieving very accurate measurements of the electron density profile up to the peak altitude. These three sources of scientific observation of the Earth ionosphere therefore provide a very complementary set of data. We compare O+ density profiles provided during nighttime by the ICON-FUV instrument and during daytime by the ICON-EUV instrument against electron density profiles measured by COSMIC-2 and ionosondes. Co-located and simultaneous observations are compared on statistical grounds, and the differences between the several methods are investigated. Particular attention is given to the most important variables, such as the altitude and the density of the F-peak, hmF2 and NmF2. The time interval considered in this study covers the whole ICON data availability period, which started on November 16, 2019. Manual screening and scaling of ionograms is performed to ensure reliable ionosonde data, while COSMIC-2 data are carefully selected using an automatic quality control algorithm. A particular attention has been brought to the geometry of the observation, because the line-of-sight integration of both airglow and radio-occultation measurements assimilates horizontal and vertical gradients. As a consequence, the local density profiles obtained by inversion of the ICON and COSMIC-2 observation cannot be exactly assimilated to vertical measurements, such as vertical incidence soundings from ionosondes. This slightly limits the reach of the interpretation of the comparison between data of different origin. However, using similar observing geometries, the comparison of ICON and COSMIC-2 data does nevertheless provide very reliable and valuable comparisons.Combining airglow, GNSS and ionosonde data to study ionospheric irregularities over low latitude

Image deconvolution via efficient sparsifying transform learning Hizli Seyreklȩstirici Dönüsüm Öǧrenme ile Görüntü Ters Evrisimi

Image deconvolution is one of the most frequently encountered inverse problems in imaging. Since natural images can be modeled sparsely in some transform domain, sparsity priors have been shown to effectively regularize these problems and enable high-quality reconstructions. In this paper, we develop a data-adaptive sparse image reconstruction approach for image deconvolution based on transform learning. Our framework adaptively learns a patch-based sparsifying transform and simultaneously reconstructs the image from its noisy blurred measurement. This is achieved by solving the resulting optimization problem using an alternating minimization algorithm which has closed-form and efficient update steps. The performance of the developed algorithm is illustrated for an application in optical imaging by considering different optical blurs and noise levels. The results demonstrate that the developed method not only improves the reconstruction quality compared to the total-variation based approach, but also is fast

EFFICIENT SPARSITY-BASED INVERSION FOR PHOTON-SIEVE SPECTRAL IMAGERS WITH TRANSFORM LEARNING

We develop an efficient and adaptive sparse reconstruction approach for the recovery of spectral images from the measurements of a photon-sieve spectral imager (PSSI). PSSI is a computational imaging technique that enables higher resolution than conventional spectral imagers. Each measurement in PSSI is a superposition of the blurred spectral images; hence, the inverse problem can be viewed as a type of multi-frame deconvolution problem involving multiple objects. The transform learning-based approach reconstructs the spectral images from these superimposed measurements while simultaneously learning a sparsifying transform. This is performed using a block coordinate descent algorithm with efficient update steps. The performance is illustrated for a variety of measurement settings in solar spectral imaging. Compared to approaches with fixed sparsifying transforms, the approach is capable of efficiently reconstructing spectral images with improved reconstruction quality

Effect of different sparsity priors on compressive photon-sieve spectral imaging

Compressive spectral imaging is a rapidly growing area yielding higher performance novel spectral imagers than conventional ones. Inspired by compressed sensing theory, compressive spectral imagers aim to reconstruct the spectral images from compressive measurements using sparse signal recovery algorithms. In this paper, first, the image formation model and a sparsity-based reconstruction approach are presented for compressive photon-sieve spectral imager. Then the reconstruction performance of the approach is analyzed using different sparsity priors. In the system, a coded aperture is used for modulation and a photon-sieve for dispersion. In the measurements, coded and blurred images of spectral bands are superimposed. Simulation results show promising image reconstruction performance from these compressive measurements

O+ density profiles provided by the ultraviolet imagers onboard ICON: comparison with radio based observations and role of the equatorial ionization anomaly

editorial reviewedThe NASA-ICON mission was dedicated to the observation of the terrestrial equatorial ionosphere between November 2019 and November 2022 from a circular orbit at about 600 km altitude. The scientific payload encompasses two ultraviolet imagers: the Far Ultraviolet Imaging Spectrograph (FUV) and the Extreme Ultra Violet (EUV) spectrograph. FUV observes the emission of the atomic oxygen doublet at 135.6 nm as well as the Lyman-Birge-Hopfield (LBH) band of N2 near 157 nm while the EUV spectrograph records daytime limb altitude profiles of terrestrial emissions in the extreme ultraviolet spectrum from 54 to 88 nm. Every 12s, based on the 135.6 nm emission for FUV and on the OII–61.7 nm and 83.4 nm emissions for EUV, both instruments provide O+ density profiles for nighttime and daytime conditions, respectively. Besides, the GNSS radio-occultation mission COSMIC-2 daily provides, since 2019, several thousands of electron density profiles above low and mid-latitudes, in addition to ground-based ionosondes delivering high-quality observations at a regular cadence. For FUV, the peak density and height are, on average, similar to radio-based observations by about 10% in density and 7 km in altitude. The EUV spectrograph provides peak density values smaller than that from other techniques by 50 to 60%, while the altitude of the peak is retrieved with a slight bias of 10 to 20 km on average. While the equatorial ionization anomaly does not have a significant influence on the EUV comparisons, it is found that the largest density differences between FUV and C2/ionosonde data are related to the ionization crests where their large density gradients and specific geometry break the spherical symmetry assumed by the inverse Abel transform to retrieve the O+ density profile. We perform a dedicated analysis of these particular cases using GNSS-TEC maps to identify the problems arising when considering multi-sensor data fusion at low-latitudes

First ICON-FUV Nighttime NmF2 and hmF2 Comparison to Ground and Space-Based Measurements

The Far Ultra Violet (FUV) ultraviolet imager onboard the NASA-ICON mission is dedicated to the observation and study of the ionosphere dynamics at mid and low latitudes. We compare O(+) density profiles provided by the ICON FUV instrument during nighttime with electron density profiles measured by the COSMIC-2 constellation (C2) and ground-based ionosondes. Co-located simultaneous observations are compared, covering the period from November 2019 to July 2020, which produces several thousands of coincidences. Manual scaling of ionogram sequences ensures the reliability of the ionosonde profiles, while C2 data are carefully selected using an automatic quality control algorithm. Photoelectron contribution coming from the magnetically conjugated hemisphere is clearly visible in FUV data around solstices and has been filtered out from our analysis. We find that the FUV observations are consistent with the C2 and ionosonde measurements, with an average positive bias lower than 1 × 10(11)e/m(3). When restricting the analysis to cases having an N(m)F(2) value larger than 5 × 10(11)e/m(3), FUV provides the peak electron density with a mean difference with C2 of 10%. The peak altitude, also determined from FUV observations, is found to be 15 km above that obtained from C2, and 38 km above the ionosonde value on average

Update of ICON-FUV hmF2 and NmF2 Comparison with External Radio Observations

peer reviewe