Optimal Bayesian fusion of large hyperspectral astronomical observations

Petremand, M.; Jalobeanu, A.; Collet, Christophe

doi:10.1016/j.stamet.2011.04.007

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Additionally, Medan et al [111] presented a Bayesian method to cross-match 5,827,988 high-proper-motion Gaia sources with various photometric surveys. Furthermore, Bayesian methods are employed to determine the probability of whether the data represent objects or the background in image fusion [112,113].…”

Section: Database Data Fusionmentioning

confidence: 99%

Artificial Intelligence in Astronomical Optical Telescopes: Present Status and Future Perspectives

Huang,

Hu,

Cai

et al. 2024

Universe

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With new artificial intelligence (AI) technologies and application scenarios constantly emerging, AI technology has become widely used in astronomy and has promoted notable progress in related fields. A large number of papers have reviewed the application of AI technology in astronomy. However, relevant articles seldom mention telescope intelligence separately, and it is difficult to understand the current development status of and research hotspots in telescope intelligence from these papers. This paper combines the development history of AI technology and difficulties with critical telescope technologies, comprehensively introduces the development of and research hotspots in telescope intelligence, conducts a statistical analysis of various research directions in telescope intelligence, and defines the merits of these research directions. A variety of research directions are evaluated, and research trends in each type of telescope intelligence are indicated. Finally, according to the advantages of AI technology and trends in telescope development, potential future research hotspots in the field of telescope intelligence are given.

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Section: Database Data Fusionmentioning

confidence: 99%

Artificial Intelligence in Astronomical Optical Telescopes: Present Status and Future Perspectives

Huang,

Hu,

Cai

et al. 2024

Universe

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“…As stated in the introduction, astronomical imaging needs long exposure times, resulting in multiple observations of the same field because of sensor saturation effect. Whereas optimal fusion methods have been developed [37], using averaged observations as in the previous sections is generally sufficient. However, information may be lost in the averaging process.…”

Section: Multiple Observationsmentioning

confidence: 99%

Extended faint source detection in astronomical hyperspectral images

Courbot

Mazet

Monfrini³

et al. 2017

Signal Processing

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International audienceThe circum-galactic medium consists in gas orbiting around galaxies, whose faintness prevents any complete and easy detection. A powerful tool to detect such pattern can be found in using hyperspectral imaging. Nevertheless, detection in hyperspectral datacubes faces various problems, including well-fitted signal and noise descriptions to ensure further discrimination. A specificity of astronomical images resides in dealing with faint and very noisy signals. In this paper, we introduce a new constrained generalized likelihood ratio test adapted to the problem and a compound test to exploit most of the available information. We also investigate the use of both spatial information and multiple observations on a single scene, to enhance robustness. Numerical experiments on synthetic data are performed to quantify the gain of the different approaches. Finally, results on real hyperspectral astronomical data are presented, which may map for the first time observation of the circum-galactic medium around faint and distant galaxie

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“…In remote sensing, it is used for geological exploration and soil characterization from a distance [ 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 ]. HSI paired with its remote sensing capability is often used in the field of astronomy for astronomic observation and space surveillance purposes [ 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ]. In addition to these, environmental applications such as drought stress measurement, pollution detection, water resource analysis, space science, and vegetation monitoring also prove HSI’s reliability [ 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 ].…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging

Huang

Mukundan

Tsao

et al. 2022

Sensors

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Forgery and tampering continue to provide unnecessary economic burdens. Although new anti-forgery and counterfeiting technologies arise, they inadvertently lead to the sophistication of forgery techniques over time, to a point where detection is no longer viable without technological aid. Among the various optical techniques, one of the recently used techniques to detect counterfeit products is HSI, which captures a range of electromagnetic data. To aid in the further exploration and eventual application of the technique, this study categorizes and summarizes existing related studies on hyperspectral imaging and creates a mini meta-analysis of this stream of literature. The literature review has been classified based on the product HSI has used in counterfeit documents, photos, holograms, artwork, and currency detection.

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Optimal Bayesian fusion of large hyperspectral astronomical observations

Cited by 6 publications

References 11 publications

Artificial Intelligence in Astronomical Optical Telescopes: Present Status and Future Perspectives

Artificial Intelligence in Astronomical Optical Telescopes: Present Status and Future Perspectives

Extended faint source detection in astronomical hyperspectral images

Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging

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