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An algorithm is presented for image prior combinations based blind deconvolution and applied to astronomical images. Using a hierarchical Bayesian framework, the unknown original image and all required algorithmic parameters are estimated simultaneously. Through utilization of variational Bayesian analysis, approximations of the posterior distributions on each unknown are obtained by minimizing the Kullback-Leibler (KL) distance, thus providing uncertainties of the estimates during the restoration process. Experimental results on both synthetic images and real astronomical images demonstrate that the proposed approaches compare favorably to other state-of-the-art reconstruction methods. [ABSTRACT FROM AUTHOR]

The article discusses how Photoshop and other image editing software are used to make astronomical images as seen in telescopes. Topics addressed include ways of precisely measuring the brightness of a star or the temperature of gas, uses of Photoshop by astronomers in removing defects in visible-light images called a charge bleed, and information on a specially developed image metadata standard, called Astronomical Visualization Metadata (AVM).

In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing (CS) theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods. [ABSTRACT FROM AUTHOR]

We show how to obtain a Bayesian estimate of the rates or numbers of signal and background events from a set of events when the shapes of the signal and background distributions are known, can be estimated, or approximated; our method works well even if the foreground and background event distributions overlap significantly and the nature of any individual event cannot be determined with any certainty. We give examples of determining the rates of gravitational-wave events in the presence of background triggers from a template bank when noise parameters are known and/or can be fit from the trigger data. We also give an example of determining globular-cluster shape, location, and density from an observation of a stellar field that contains a nonuniform background density of stars superimposed on the cluster stars. [ABSTRACT FROM AUTHOR]

Detecting weak celestial source signals from massive radio data is a very challenging task because the radiation received by radio telescope is very weak and prone to disturbances. In order to detect these weak signals, we propose a two-stage object detection method that performs more finely in computer vision tasks. The novelty of the proposed method is to combine traditional soft thresholding denoising methods with attention mechanisms in deep neural networks. We propose a channel attention shrinkage network as the backbone of the object detection model to extract the features of weak signals from celestial sources by removing noise-related information. Moreover, targeting the characteristics of celestial source fringes in phase images, we propose a cluster-based anchor boxes generation algorithm to improve the accuracy of fringes position detection. We also introduce the CIoU loss function to improve the performance of the model because of the large aspect ratio of the celestial source fringes in the phase image. We generate simulated celestial source fringes data based on the parameters of the observation system to train our model and conduct experiments to evaluate the performance of the proposed algorithm. Our model obtains satisfactory detection accuracy and accurate for the location of celestial source fringes. [ABSTRACT FROM AUTHOR]

The article reports on the first image of a black hole's event horizon. It mentions the work of the Event Horizon Telescope to process the image of Sagittarius A* from the M87 galaxy, the support the image gives to Einstein's theory of relativity, and how this will help the study of the accretion process.

The article discusses and presents an image of the Whirlpool Galaxy, noting that it was created by combining optical and x-ray data. Topics include the fact that this galaxy is the result of two galaxies which merged and the x-ray emissions from a dense neutron star in the galaxy.

The article reports that researchers from the Instituto de Astrofísica de Canarias in Santa Cruz de Tenerife, Spain, improved the process for combining the images taken by Hubble telescope's Wide Field Camera 3 and produced an even more detailed snapshot.

The author discusses image processing in astronomy and how it is practiced by professional astronomers. The author describes his visit at the Mount Lemmon SkyCenter in Mount Lemmon, Arizona. It mentions the importance of understanding the power of statistics and nature of light in astronomical image processing that help in identification and management of unwanted sources of signals and noise.

The article offers instructions on cosmic imaging techniques, focusing on using the Adobe Photoshop image editing software to achieve double color layer for natural-looking astronomical images.

In this article the author discusses a technique for sharpening astronomical photographs, called deconvolution. Topics include image-processing software called CCD Sharp from Santa Barbara Instrument Group, the drawback of using the software for sharpening an image, the importance of having a good signal-to-noise ratio when attempting deconvolution, and estimating the point-spread function (PSF).