Restoration of hyperspectral astronomical data with spectrally varying blur

International audienceIn this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. We specifically address two topics: (i) the design of a fast approximation of spectrally varying operators and (ii) the comparison between two kind of regularization functions: quadratic and spatial sparsity functions. We illustrate this method with simulations coming from the Multi Unit Spectroscopic Explorer (MUSE) instrument. It shows the clear increase of the spatial resolution provided by our method as well as its denoising capability

Exploration of the use of digital micromirror devices for highly multiplexed spectroscopy applications in astronomy

Highly multiplexed spectroscopic capabilities are critical to future astronomy space missions. Such capabilities enable large samples of spectral data to be collected in an efficient manner. The individual mirrors of a Digital Micromirror Device (DMD) can serve as slits in a multi-object spectrograph (MOS). This work explores several areas vital to the inclusion of DMDs in future astronomy missions: space qualification, optical performance, and the implementation of Hadamard Transform Spectral Imaging (HTSI). While DMDs were not designed for space, this work reports on testing that demonstrates that the devices can withstand the environmental conditions of a space mission. The optical properties of a DMD ultimately drive the wavelength range and quality of spectral data obtained from a DMD-based MOS. We have characterized the reflectance and contrast ratio of various DMDs from near ultra-violet through visible wavelengths and discuss the results. This work also discusses efforts in expanding the spectral sensitivity of DMDs. Maximizing spectral information over a spatial field of view (FoV) on the sky is highly desirable. In the multi-object spectroscopy mode, individual DMD micromirrors are selected to generate a sparse sample of spectra at individual locations. Additionally, a DMD can be used for integral field spectroscopy (IFS) by forming a long slit from a line of micromirrors, which is then altered to effectively scan across the FoV. In this work we evaluate an alternative technique, HTSI. HTSI has the advantage of a gain in signal-to-noise ratio (SNR) as compared to direct measurements with a long slit, when the observed signals are not photon-noise dominated. We have simulated the performance of HTSI with a DMD-based MOS to identify the limitations of the technique and scenarios where it is most advantageous. With both MOS and IFS capabilities, a DMD-based instrument is a versatile asset fit for a variety of astronomy missions

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

On advanced estimation techniques for exoplanet detection and characterization using ground-based coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We provide a formal comparison of techniques through a blind data challenge and evaluate performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image

This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image

Recent Advances in Image Restoration with Applications to Real World Problems

In the past few decades, imaging hardware has improved tremendously in terms of resolution, making widespread usage of images in many diverse applications on Earth and planetary missions. However, practical issues associated with image acquisition are still affecting image quality. Some of these issues such as blurring, measurement noise, mosaicing artifacts, low spatial or spectral resolution, etc. can seriously affect the accuracy of the aforementioned applications. This book intends to provide the reader with a glimpse of the latest developments and recent advances in image restoration, which includes image super-resolution, image fusion to enhance spatial, spectral resolution, and temporal resolutions, and the generation of synthetic images using deep learning techniques. Some practical applications are also included