Multiband Imaging Research Articles

Variational model with nonstandard growth conditions for restoration of satellite optical images using synthetic aperture radar

In this paper, the problem of restoration of cloud contaminated optical images is studied in the case when we have no information about brightness of such images in the damage region. We propose a new variational approach for exact restoration of optical multi-band images utilising Synthetic Aperture Radar (EOS – Spatial Data Analytics, GIS Software, Satellite Imagery – is a cloud-based platform to derive remote sensing data and analyse satellite imagery for business and science purposes) images of the same regions. We prove existence of solutions, propose an alternating minimisation method for computing them, prove convergence of this method to weak solutions of the original problem and derive optimality conditions.

The resolved chemical abundance properties within the interstellar medium of star-forming galaxies at z≈ 1.5

ABSTRACT We exploit the unprecedented depth of integral field data from the KMOS Ultra-deep Rotational Velocity Survey (KURVS) to analyse the strong (Hα) and forbidden ([N ii], [S ii]) emission line ratios in 22 main-sequence galaxies at $z\, \approx \, 1.5$. Using the [N ii]/Hα emission-line ratio, we confirm the presence of the stellar mass – gas-phase metallicity relation at this epoch, with galaxies exhibiting on average 0.13 ± 0.04 dex lower gas-phase metallicity (12 + log(O/H)M13 = 8.40 ± 0.03) for a given stellar mass (log10(M*[M⊙] = 10.1 ± 0.1) .than local main-sequence galaxies. We determine the galaxy-integrated [S ii] doublet ratio, with a median value of [S ii]λ6716/λ6731 = 1.26 ± 0.14 equivalent to an electron density of log10(ne[cm−3]) = 1.95 ± 0.12. Utilising CANDELS HST multi-band imaging we define the pixel surface-mass and star-formation rate density in each galaxy and spatially resolve the fundamental metallicity relation at $z\, \approx \, 1.5$, finding an evolution of 0.05 ± 0.01 dex compared to the local relation. We quantify the intrinsic gas-phase metallicity gradient within the galaxies using the [N ii]/Hα calibration, finding a median annuli-based gradient of ΔZ/ΔR = −0.015 ± 0.005 dex kpc−1. Finally, we examine the azimuthal variations in gas-phase metallicity, which show a negative correlation with the galaxy integrated star-formation rate surface density ($r_{\rm s}\,$ = −0.40, ps = 0.07) but no connection to the galaxies kinematic or morphological properties nor radial variations in stellar mass surface density or star formation rate surface density. This suggests both the radial and azimuthal variations in interstellar medium properties are connected to the galaxy integrated density of recent star formation.

New view of the Balmer-Kapteyn region: Cryptomare distribution and formation

Context. The cryptomare in the Balmer-Kapteyn region is the oldest one on the Moon. Determining the extent and formation of this feature can deepen our understanding of early mare volcanism and help establish temporal and spatial constraints on lunar thermal and volcanic history. Aims. This paper focuses on the identification of lunar cryptomaria and figuring out their formation processes. Methods. We used the Global WAC digital terrain model to analyze the terrain. We built a mathematical model using support vector machines and input Kaguya Multiband Imager data to estimate oxide concentrations in the Balmer-Kapteyn region. We used the Chandrayaan-1 Moon Mineralogy Mapper (M3) to analyze the minerals. We improved the cryptomare identification model to increase the accuracy of basalt identification in the cryptomare region. Finally, we used three methods to estimate the ejecta thickness of the target basin to the Balmer-Kapteyn region. Results. New Al2O3, CaO, FeO, MgO, and TiO2 maps were generated using the Kaguya Multiband Imager and a novel machine-learning model. As a result, the extent of the cryptomare in the Balmer-Kapteyn region was redefined and the formation process of the cryptomare in the Balmer-Kapteyn region was divided into five formation stages: Balmer basin formation, ejecta coverage from the Pre-Nectarian and Nectarian large impact basins, mare basalt filling, ejecta secondary coverage of high-albedo materials, and exposure of mare basalts. Conclusions. We found that the bottom of the Crater Vendelinus is likely to hide ancient mare basalt. Moreover, the high-aluminum mare basalt of the cryptomare is different from the composition of the exposed mare basalts in Mare Fecunditatis and Crater Vendelinus. The high-albedo material covering the cryptomare in the Balmer-Kapteyn region could have come from the Langrenus, Petavius, Humboldt, La Perouse, and Ansgarius Craters, along with some from the Orientale Basin impact event or potentially from the Imbrium Basin impact event.

No-Reference Quality Assessment of Pan-Sharpening Images with Multi-Level Deep Image Representations

The Pan-Sharpening (PS) techniques provide a better visualization of a multi-band image using the high-resolution single-band image. To support their development and evaluation, in this paper, a novel, accurate, and automatic No-Reference (NR) PS Image Quality Assessment (IQA) method is proposed. In the method, responses of two complementary network architectures in a form of extracted multi-level representations of PS images are employed as quality-aware information. Specifically, high-dimensional data are separately extracted from the layers of the networks and further processed with the Kernel Principal Component Analysis (KPCA) to obtain features used to create a PS quality model. Extensive experimental comparison of the method on the large database of PS images against the state-of-the-art techniques, including popular NR methods adapted in this study to the PS IQA, indicates its superiority in terms of typical criteria.

Optical Confirmation of X-Ray-selected Galaxy Clusters from the Swift AGN and Cluster Survey with MDM and Pan-STARRS Data. III

Abstract To understand structure formation in the universe and impose stronger constraints on the cluster mass function and cosmological models, it is important to have large galaxy cluster catalogs. The Swift AGN and Cluster Survey is a serendipitous X-ray survey aimed at building a large statistically selected X-ray cluster catalog with 442 cluster candidates in its first release. Our initial SDSS follow-up study confirmed 50% of clusters in the Sloan Digital Sky Survey footprint as z < 0.5 clusters. Here we present further optical follow-up analysis of 248 (out of 442) cluster candidates from the Swift cluster catalog using multiband imaging from the MDM 2.4 m telescope and the Pan-STARRS survey. We report the optical confirmation of 55 clusters with >3σ galaxy overdensities and detectable red sequences in the color–magnitude space. The majority of these confirmed clusters have redshifts z < 0.6. The remaining candidates are potentially higher-redshift clusters that are excellent targets for infrared observations. We report the X-ray luminosity and the optical richness for these confirmed clusters. We also discuss the distinction between X-ray and optical observables for the detected and nondetected cluster candidates.

Thermal imaging of dust hiding the black hole in NGC 1068.

In the widely accepted 'unified model'1 solution of the classification puzzle of active galactic nuclei, the orientation of a dusty accretion torus around the central black hole dominates their appearance. In 'type-1' systems, the bright nucleus is visible at the centre of a face-on torus. In 'type-2' systems the thick, nearly edge-on torus hides the central engine. Later studies suggested evolutionary effects2 and added dusty clumps and polar winds3 but left the basic picture intact. However,recent high-resolution images4 of the archetypal type-2 galaxy NGC 10685,6, suggested a more radical revision. The images displayed a ring-like emission feature that was proposed to be hot dust surrounding the black hole at the radius where the radiation from the central engine evaporates the dust. That ring is too thin and too far tilted from edge-on to hide the central engine, and ad hoc foreground extinction is needed to explain the type-2 classification. These images quickly generated reinterpretations of the dichotomy between types 1 and 27,8. Here we present new multi-band mid-infrared images of NGC 1068 that detail the dust temperature distribution and reaffirm the original model. Combined with radio data (J.F.G. and C.M.V.I., manuscript in preparation), our maps locate the central engine that is below the previously reported ring and obscured by a thick, nearly edge-on disk, as predicted by the unified model. We also identify emission from polar flows and absorbing dust that is mineralogically distinct from that towards the Milky Way centre.

Third data release of the Hyper Suprime-Cam Subaru Strategic Program

AbstractThis paper presents the third data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field multi-band imaging survey with the Subaru 8.2 m telescope. HSC-SSP has three survey layers (Wide, Deep, and UltraDeep) with different area coverages and depths, designed to address a wide array of astrophysical questions. This third release from HSC-SSP includes data from 278 nights of observing time and covers about 670 deg2 in all five broad-band filters (grizy) at the full depth (∼26 mag at 5σ depending on filter) in the Wide layer. If we include partially observed areas, the release covers 1470 deg2. The Deep and UltraDeep layers have $\sim\! 80\%$ of the originally planned integration times, and are considered done, as we have slightly changed the observing strategy in order to compensate for various time losses. There are a number of updates in the image processing pipeline. Of particular importance is the change in the sky subtraction algorithm; we subtract the sky on small scales before the detection and measurement stages, which has significantly reduced the number of false detections. Thanks to this and other updates, the overall quality of the processed data has improved since the previous release. However, there are limitations in the data (for example, the pipeline is not optimized for crowded fields), and we encourage the user to check the quality assurance plots as well as a list of known issues before exploiting the data. The data release website is 〈https://hsc-release.mtk.nao.ac.jp〉.

VLT/MUSE Observations of SDSS J1029+2623: Toward a High-precision Strong Lensing Model*

Abstract We present a strong lensing analysis of the galaxy cluster SDSS J1029+2623 at z = 0.588, one of the few currently known lens clusters with multiple images of a background (z = 2.1992) quasar with a measured time delay. We use archival Hubble Space Telescope multiband imaging and new Multi Unit Spectroscopic Explorer follow-up spectroscopy to build an accurate lens mass model, a crucial step toward future cosmological applications. The spectroscopic data enable the secure identification of 57 cluster members and of two nearby perturbers along the line of sight. We estimate the inner kinematics of a subset of 20 cluster galaxies to calibrate the scaling relations parameterizing the sub-halo mass component. We also reliably determine the redshift of four multiply imaged sources, provide a tentative measurement for one system, and report the discovery of a new four-image system. The final catalog comprises 26 multiple images from seven background sources, spanning a wide redshift range, from 1.02 to 5.06. We present two parametric lens models, with slightly different cluster mass parameterizations. The observed positions of the multiple images are accurately reproduced within approximately 0.″2, the three image positions of the quasar within only ∼0.″1. We estimate a cluster projected total mass of M(<300 kpc) ∼ 2.1 × 1014 M ⊙, with a statistical uncertainty of a few percent. Both models, which include a small galaxy close to one of the quasar images, predict magnitude differences and time delays between the quasar images that are consistent with the observations.

Global Distribution and Geological Context of Co‐Existing Occurrences of Olivine‐Rich and Plagioclase‐Rich Materials on the Lunar Surface

AbstractWe examined the global distribution and geological context of lunar sites where olivine‐ and plagioclase‐rich materials co‐exist. These sites are areas showing plagioclase‐rich spectra adjacent to areas showing olivine‐rich spectra, and they extend over several hundreds of meters on the lunar surface. From an analysis of the high‐spatial‐resolution data obtained from the SELENE (Kaguya) multiband imager, we identified 14 co‐existing occurrences among 49 olivine‐rich sites located around large impact basins. We found that the co‐existing occurrences are limited to a few sites among the olivine‐rich sites in the Moscoviense, Crisium, and Imbrium basins, while six of seven olivine‐rich sites in the Schrödinger basin show co‐existing occurrence. The geological features between the co‐existing occurrences and the olivine‐rich sites without plagioclase‐rich materials showed no clear difference, but both types of site are found at fresh geological features located around the peak rings of impact basins. These results may suggest that the co‐existing occurrences are closely related to the material heterogeneity of the peak ring regions. The heterogeneity could be formed by mixing of the olivine‐rich mantle and the anorthosite‐rich crust during impact basin formation, or it might be a reflection of the compositional heterogeneity of the lunar lower crust. For future sample return missions, the detailed information on the co‐existing occurrences presented here might be useful for a sampling strategy to select a “one‐stop” site that provides important information for the overall characterization of lunar mantle and crustal materials.

Comparison of Classical Methods and Mask R-CNN for Automatic Tree Detection and Mapping Using UAV Imagery

Detecting and mapping individual trees accurately and automatically from remote sensing images is of great significance for precision forest management. Many algorithms, including classical methods and deep learning techniques, have been developed and applied for tree crown detection from remote sensing images. However, few studies have evaluated the accuracy of different individual tree detection (ITD) algorithms and their data and processing requirements. This study explored the accuracy of ITD using local maxima (LM) algorithm, marker-controlled watershed segmentation (MCWS), and Mask Region-based Convolutional Neural Networks (Mask R-CNN) in a young plantation forest with different test images. Manually delineated tree crowns from UAV imagery were used for accuracy assessment of the three methods, followed by an evaluation of the data processing and application requirements for three methods to detect individual trees. Overall, Mask R-CNN can best use the information in multi-band input images for detecting individual trees. The results showed that the Mask R-CNN model with the multi-band combination produced higher accuracy than the model with a single-band image, and the RGB band combination achieved the highest accuracy for ITD (F1 score = 94.68%). Moreover, the Mask R-CNN models with multi-band images are capable of providing higher accuracies for ITD than the LM and MCWS algorithms. The LM algorithm and MCWS algorithm also achieved promising accuracies for ITD when the canopy height model (CHM) was used as the test image (F1 score = 87.86% for LM algorithm, F1 score = 85.92% for MCWS algorithm). The LM and MCWS algorithms are easy to use and lower computer computational requirements, but they are unable to identify tree species and are limited by algorithm parameters, which need to be adjusted for each classification. It is highlighted that the application of deep learning with its end-to-end-learning approach is very efficient and capable of deriving the information from multi-layer images, but an additional training set is needed for model training, robust computer resources are required, and a large number of accurate training samples are necessary. This study provides valuable information for forestry practitioners to select an optimal approach for detecting individual trees.

MAPPING OIL SPILLS ON SEA SURFACE FROM SENTINEL 2 IMAGES USING PRINCIPAL COMPONENTS AND CATEGORICAL BOOSTING

Abstract. A large oil spill in Iloilo Straight that occurred on July 3, 2020, as well as a possible deliberate, small but frequent oil spill and surfactant contamination in Manila Bay, were mapped. The method employs the Sentinel 2-1C image, which is transformed into principal components to reveal the presence of oil spills and possibly surfactants. Additionally, a gradient boosting algorithm was trained to discriminate between pixels that were contaminated with oil and those that were not. The multi-band image with three principal components with a 99% cumulative explained variance ratio highlights the occurrence of an oil spill in Iloilo Straight. Further, the classified image produced by pixel-based classification clearly distinguishes between water and oil pixels in the said area. The methodology was applied to a Sentinel 2-1C image of Manila Bay, with pixels observed/identified as oil and classified as well. The highest density of supposedly oil-contaminated pixels (large or small but frequent) was observed on the eastern side of Manila Bay (Bataan). While there were no documented oil spills concurrent to the satellite image used, historical reports on the area indicate that the likelihood of an oil spill is extremely high due to the massive amount of shipping activity. Pixels supposedly contaminated by oil spills also occur in areas near ports where oil spills could occur as a result of ship operations. Pixels with the same properties as oil contamination are also visible in areas adjacent to fishponds and aquaculture, where phytoplankton and fish contribute to surfactant contamination.

Multispectral Image under Tissue Classification Algorithm in Screening of Cervical Cancer.

The objectives of this study were to improve the efficiency and accuracy of early clinical diagnosis of cervical cancer and to explore the application of tissue classification algorithm combined with multispectral imaging in screening of cervical cancer. 50 patients with suspected cervical cancer were selected. Firstly, the multispectral imaging technology was used to collect the multispectral images of the cervical tissues of 50 patients under the conventional white light waveband, the narrowband green light waveband, and the narrowband blue light waveband. Secondly, the collected multispectral images were fused, and then the tissue classification algorithm was used to segment the diseased area according to the difference between the cervical tissues without lesions and the cervical tissues with lesions. The difference in the contrast and other characteristics of the multiband spectrum fusion image would segment the diseased area, which was compared with the results of the disease examination. The average gradient, standard deviation (SD), and image entropy were adopted to evaluate the image quality, and the sensitivity and specificity were selected to evaluate the clinical application value of discussed method. The fused spectral image was compared with the image without lesions, it was found that there was a clear difference, and the fused multispectral image showed a contrast of 0.7549, which was also higher than that before fusion (0.4716), showing statistical difference (P < 0.05). The average gradient, SD, and image entropy of the multispectral image assisted by the tissue classification algorithm were 2.0765, 65.2579, and 4.974, respectively, showing statistical difference (P < 0.05). Compared with the three reported indicators, the values of the algorithm in this study were higher. The sensitivity and specificity of the multispectral image with the tissue classification algorithm were 85.3% and 70.8%, respectively, which were both greater than those of the image without the algorithm. It showed that the multispectral image assisted by tissue classification algorithm can effectively screen the cervical cancer and can quickly, efficiently, and safely segment the cervical tissue from the lesion area and the nonlesion area. The segmentation result was the same as that of the doctor's disease examination, indicating that it showed high clinical application value. This provided an effective reference for the clinical application of multispectral imaging technology assisted by tissue classification algorithm in the early screening and diagnosis of cervical cancer.

HCNNet: A Hybrid Convolutional Neural Network for Spatiotemporal Image Fusion

In recent years, leaps and bounds have developed spatiotemporal fusion (STF) methods for remote sensing (RS) images based on deep learning. However, most existing methods utilize 2D convolution (Conv) to explore features. 3D Conv can explore time-dimensional features, but it requires more memory footprint and is rarely used. In addition, the current STF methods based on convolutional neural networks (CNNs) are mainly the following two: 1) Use 2D Conv to extract features from multiple bands of the input image together and fuse the features to predict the multiband image directly; 2) Use 2D Conv to extract features from individual bands of the image, predict the reflectance data of individual bands, and finally stack the predicted individual bands directly to synthesize the multiband image. The former method does not sufficiently consider the spectral and reflectance differences between different bands, and the latter does not consider the similarity of spatial structures between adjacent bands and the spectral correlation. To solve these problems, we propose a 2D/3D hybrid convolution neural network (CNN) called HCNNet, in which the 2D-CNN branch extracts the spatial information features of single-band image, and the 3D-CNN branch extracts spatiotemporal features of single-band images. After fusing the features of the dual branches, we introduce neighboring band features to share spatial information so that the information is complementary to obtain single-band features and images, and finally stack each single-band image to generate multiband images. Visual assessment and metric evaluation of the three publicly available datasets showed that our method predicted better images compared to the five methods.

Tunable triple-band millimeter-wave absorbing metasurface based on nematic liquid crystal

We propose and design a tunable triple-band millimeter-wave absorbing metasurface based on nematic liquid crystal (NLC). Numerical results based on both effective circuit model and full-wave simulations verify the triple-band absorption property. All triple absorption peaks can be shifted by changing the bias voltage applied to the nematic liquid crystal. We fabricate and measure a triple-band absorbing metasurface sample, which covers 100 × 100 mm2 and is composed of 20 × 20 unit cells. In experiments, when no bias voltage is applied to the NLC layer, the resonant frequencies of the absorbing metasurface are 25.4, 28.7, and 32.8 GHz, respectively. When a 5-V bias voltage is applied, all the absorbing peaks redshift, and a frequency tunability range of 9.5%, 9.1%, and 8.58% is observed in three resonant frequencies, respectively. The experimental results are in good agreement with the numerical simulations. The proposed tunable absorbing metasurface provides a way forward for the realization of tunable millimeter-wave metasurface devices that can be applied in multi-band detection and imaging.

Diagnosing DASH: A Catalog of Structural Properties for the COSMOS-DASH Survey

Abstract We present the H 160 morphological catalogs for the COSMOS-DASH survey, the largest area near-IR survey using HST-WFC3 to date. Utilizing the “Drift And SHift” observing technique for HST-WFC3 imaging, the COSMOS-DASH survey imaged approximately 0.5 deg2 of the UltraVISTA deep stripes (0.7 deg2, when combined with archival data). Global structural parameters are measured for 51,586 galaxies within COSMOS-DASH using GALFIT (excluding the CANDELS area) with detection using a deep multi-band HST image. We recover consistent results with those from the deeper 3D-HST morphological catalogs, finding that, in general, sizes and Sérsic indices of typical galaxies are accurate to limiting magnitudes of H 160 &lt; 23 and H 160 &lt; 22 ABmag, respectively. In size-mass parameter space, galaxies in COSMOS-DASH demonstrate robust morphological measurements out to z ∼ 2 and down to log ( M ⋆ / M ⊙ ) ∼ 9 . With the advantage of the larger area of COSMOS-DASH, we measure a flattening of the quiescent size-mass relation below log ( M ⋆ / M ⊙ ) ∼ 10.5 that persists out to z ∼ 2. We show that environment is not the primary driver of this flattening, at least out to z = 1.2, whereas internal physical processes may instead govern the structural evolution.

Usefulness of the automated multiband imaging system for EUS-FNA biopsy specimen evaluation in patients with upper gastrointestinal subepithelial lesions.

Sample isolation processing by stereomicroscopy (SIPS) was recently introduced as an alternative to rapid on-site cytologic evaluation and showed high accuracy for use in pathologic diagnoses. SIPS is a useful, but slightly complicated procedure; therefore, a new, more straightforward method for the objective estimation of the core tissue amount required during the sampling is desirable. We evaluated the usefulness of the automated multiband imaging system (AMUS) for calculating whitish core amounts in EUS-FNA biopsy (EUS-FNAB) samples from patients with subepithelial lesions (SELs). Four EUS-FNAB specimens per patient were obtained from 20 patients with upper gastrointestinal SELs. The correlation between the whitish core amount calculated by AMUS, length of the manually measured whitish cores (stereomicroscopically visible white core [SVWC]), and sample suitability for pathologic evaluation were analyzed. We identified 13 patients with gastrointestinal stromal tumors, five with leiomyomas, one with a schwannoma, and one with an ectopic pancreas. The histological diagnostic accuracy was 100%, median SVWC length was 9 mm, and median whitish core area, calculated using AMUS, was 10 mm2. SVWC length correlated with whitish core amount (ρ = 0.81, P < 0.01) and adequacy score (ρ = 0.54, P < 0.01). Whitish core amount correlated with adequacy score (ρ = 0.54, P < 0.01). The area under the receiver-operating characteristic curve calculated for whitish core amount with respect to the histological diagnosis was 0.83 (P < 0.01; cutoff ≥4 mm2, sensitivity 98.4%). AMUS, a simple on-site verification instrument, is an alternative to SIPS for determining the appropriate SEL tissue sampling quantity with high diagnostic accuracy.

Segmentation of Multi-Band Images Using Watershed Arcs

Watershed Arcs Removal for node-weighted graphs method addressed the over-segmentation problem of classical watershed transformation, in a significantly shorter run-time. In this study, a variation of Watershed Arcs Removal is proposed that generates hierarchical partitioning in an edge-weighted graph. In the proposed method, regions are grown from the nodes having high local similarity to find the initial arcs, and neighbouring regions are merged by gradually removing arcs with low local dissimilarity. The arcs to be removed in a level are selected solely from the arc-graph constructed from the existing arcs in the previous level, weighted by their local dissimilarity. In contrast to the node-weighted variation, a strategy is employed here to preserve the critical arcs. Although the proposed method can be effectively applied to any multi-band image by transforming it into an edge-weighted graph, in this study we evaluated its performance particularly in RGB image segmentation.

Guided Nonlocal Patch Regularization and Efficient Filtering-Based Inversion for Multiband Fusion

In multiband fusion, an image with a high spatial and low spectral resolution is combined with an image with a low spatial but high spectral resolution to produce a single multiband image having high spatial and spectral resolutions. This comes up in remote sensing applications such as pansharpening (MS+PAN), hyperspectral sharpening (HS+PAN), and HS-MS fusion (HS+MS). Remote sensing images are textured and have repetitive structures. Motivated by nonlocal patch-based methods for image restoration, we propose a convex regularizer that (i) takes into account long-distance correlations, (ii) penalizes patch variation, which is more effective than pixel variation for capturing texture information, and (iii) uses the higher spatial resolution image as a guide image for weight computation. We come up with an efficient ADMM algorithm for optimizing the regularizer along with a standard least-squares loss function derived from the imaging model. The novelty of our algorithm is that by expressing patch variation as filtering operations and by judiciously splitting the original variables and introducing latent variables, we are able to solve the ADMM subproblems efficiently using FFT-based convolution and soft-thresholding. As far as the reconstruction quality is concerned, our method is shown to outperform state-of-the-art variational and deep learning techniques.

Stray light analysis by ray tracing simulation for the wide-angle multiband camera OROCHI onboard the Martian Moons eXploration (MMX) spacecraft

• Ray tracing analysis was conducted to reduce stray light of OROCHI onboard the MMX. • OROCHI’s optical system is simulated and its CCD reflectance was measured. • Our techniques are incorporated into the preliminary design of OROCHI. The Martian Moons eXploration (MMX) spacecraft is equipped with two cameras, i.e., the TElescopic Nadir imager for GeOmOrphology (TENGOO) and the Optical Radiometer composed Of CHromatic Imagers (OROCHI), for the scientific observation of the Martian moon Phobos. OROCHI is a wide-angle multiband camera system comprising seven cameras with different bandpass filters and one monochromatic camera in the visible and near-infrared range. Thus, OROCHI can simultaneously obtain multiband images. Previous space observations have revealed that the reflection spectra of Phobos exhibit regional differences, including a red unit and a blue unit with weak redness. Moreover, Phobos shows an absorption band near 650 nm, attributed to the red unit of Phobos. Global observations using OROCHI require the determination of such regional variations with high precision; therefore, we must reduce noise in the optical system design. In this study, to meet this requirement, we focus on stray light reduction. Stray light is a source of noise generated by reflections at surfaces of optical components (e.g., sensors, filters, lenses, and lens barrels). We design simulation models of the OROCHI optical system, measure the reflectance of its charge-coupled device (CCD) image sensor, and conduct stray light analysis via ray tracing. We estimate the ratio of the stray light intensity to the target signal intensity by deriving both the reflected (constituting stray light) and unreflected rays. We show that placing the filter away from the sensor and reducing the reflectances of the filter and lenses effectively reduce stray light. Such approaches are incorporated into the preliminary design of OROCHI.

TOI-2285b: A 1.7 Earth-radius planet near the habitable zone around a nearby M dwarf

Abstract We report the discovery of TOI-2285b, a sub-Neptune-sized planet transiting a nearby (42 pc) M dwarf with a period of 27.3 d. We identified the transit signal from the Transiting Exoplanet Survey Satellite photometric data, which we confirmed with ground-based photometric observations using the multiband imagers MuSCAT2 and MuSCAT3. Combining these data with other follow-up observations including high-resolution spectroscopy with the Tillinghast Reflector Echelle Spectrograph, high-resolution imaging with the SPeckle Polarimeter, and radial velocity (RV) measurements with the InfraRed Doppler instrument, we find that the planet has a radius of $1.74 \pm 0.08\, R_\oplus$, a mass of $\lt \!\!19.5\,M_\oplus$ ($95\%$ c.l.), and an insolation flux of 1.54 ± 0.14 times that of the Earth. Although the planet resides just outside the habitable zone for a rocky planet, if the planet harbors an H2O layer under a hydrogen-rich atmosphere, then liquid water could exist on the surface of the H2O layer depending on the planetary mass and water mass fraction. The bright host star in the near-infrared (Ks = 9.0) makes this planet an excellent target for further RV and atmospheric observations to improve our understanding of the composition, formation, and habitability of sub-Neptune-sized planets.