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相关论文: Differencing and Coadding JWST Images with Matched…

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As the James Webb Space Telescope (JWST) has become fully operational, early-release data are now available to begin building the tools and calibrations for precision point-source photometry and astrometry in crowded cluster environments.…

太阳与恒星天体物理 · 物理学 2022-09-28 D. Nardiello , L. R. Bedin , A. Burgasser , M. Salaris , S. Cassisi , M. Griggio , M. Scalco

Image subtraction is essential for transient detection in time-domain astronomy. The point spread function (PSF), photometric scaling, and sky background generally vary with time and across the field-of-view for imaging data taken with…

天体物理仪器与方法 · 物理学 2022-09-14 Lei Hu , Lifan Wang , Xingzhuo Chen , Jiawen Yang

We present a detailed analysis of the point spread function (PSF) of JWST NIRCam imaging in eight filters: F070W, F115W, F150W, F200W, F277W, F356W, F444W, and F480M, using publicly available data. Spatial variations in the PSF FWHM…

星系天体物理 · 物理学 2023-04-28 Ming-Yang Zhuang , Yue Shen

The key features of the MATPHOT algorithm for precise and accurate stellar photometry and astrometry using discrete Point Spread Functions are described. A discrete Point Spread Function (PSF) is a sampled version of a continuous PSF which…

天体物理学 · 物理学 2009-11-11 Kenneth J. Mighell

We introduce a novel framework for upsampled Point Spread Function (PSF) modeling using pixel-level Bayesian inference. Accurate PSF characterization is critical for precision measurements in many fields including: weak lensing, astrometry,…

We present the application of the image coaddition algorithm, Up-sampling and PSF Deconvolution Coaddition (UPDC), for stacking multiple exposure images captured by the James Webb Space Telescope (JWST) Near-Infrared Camera (NIRCam). By…

A new method is presented for determining the Point Spread Function (PSF) of images that lack bright and isolated stars. It is based on the same principles as the MCS (Magain, Courbin, Sohy, 1998) image deconvolution algorithm. It uses the…

天体物理学 · 物理学 2009-11-11 P. Magain , F. Courbin , M. Gillon , S. Sohy , G. Letawe , V. Chantry , Y. Letawe

We present a new algorithm for estimating the Point Spread Function (PSF) in wide-field astronomical images with extreme source crowding. Robust and accurate PSF estimation in crowded astronomical images dramatically improves the fidelity…

图像与视频处理 · 电气工程与系统科学 2021-02-09 Brendt Wohlberg , Przemek Wozniak

Simulated images are essential in algorithm development and instrument testing for optical telescopes. During real observations, images obtained by optical telescopes are affected by spatially variable point spread functions (PSFs), a…

天体物理仪器与方法 · 物理学 2025-02-17 Zeyu Bai , Peng Jia , Jiameng Lv , Xiang Zhang , Wennan Xiang , Lin Nie

Accurate astrometry and photometry of saturated and coronagraphic point spread functions (PSFs) are fundamental to both ground- and space-based high contrast imaging projects. For ground-based adaptive optics imaging, differential…

天体物理学 · 物理学 2008-11-26 C. Marois , D. Lafreniere , B. Macintosh , R. Doyon

A point spread function (PSF) describes the distribution of light for a pure point source in an astronomical image due to the optics of the instrument. An accurate PSF is key for deconvolution, point source photometry and source removal.…

天体物理仪器与方法 · 物理学 2025-07-28 Ava Polzin

We present STARRED, a Point Spread Function (PSF) reconstruction, two-channel deconvolution, and light curve extraction method designed for high-precision photometric measurements in imaging time series. An improved resolution of the data…

天体物理仪器与方法 · 物理学 2024-07-25 Martin Millon , Kevin Michalewicz , Frédéric Dux , Frédéric Courbin , Philip J. Marshall

Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are necessary, as in optimal photometry…

天体物理仪器与方法 · 物理学 2021-02-03 Teresa Symons , Michael Zemcov , James Bock , Yun-Ting Cheng , Brendan Crill , Christopher Hirata , Stephanie Venuto

We present the implementation and use of algorithms for matching point-spread functions (PSFs) within the Pan-STARRS Image Processing Pipeline (IPP). PSF-matching is an essential part of the IPP for the detection of supernovae and…

天体物理仪器与方法 · 物理学 2019-01-30 Paul A. Price , Eugene A. Magnier

Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution…

天体物理仪器与方法 · 物理学 2013-05-30 Steven Hartung , Hemant Shukla , J. Patrick Miller , Carlton Pennypacker

We present criteria for separately classifying stars and unresolved background galaxies in photometric catalogs generated with the point spread function (PSF) fitting photometry software DOLPHOT from images taken of Draco II, WLM, and M92…

Image subtraction in astronomy is a tool for transient object discovery and characterization, particularly useful in wide fields, and is well suited for moving or photometrically varying objects such as asteroids, extra-solar planets and…

天体物理仪器与方法 · 物理学 2013-01-09 Steven Hartung

Uncertainty in the wide-angle Point Spread Function (PSF) at large angles (tens of arcseconds and beyond) is one of the dominant sources of error in a number of important quantities in observational astronomy. Examples include the stellar…

Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as PSF,…

天体物理仪器与方法 · 物理学 2016-12-07 Alexandre Boucaud , Marco Bocchio , Alain Abergel , François Orieux , Hervé Dole , Mohamed Amine Hadj-Youcef

This Point spread function (PSF) plays a crucial role in many computational imaging applications, such as shape from focus/defocus, depth estimation, and fluorescence microscopy. However, the mathematical model of the defocus process is…

计算机视觉与模式识别 · 计算机科学 2022-09-20 Renzhi He , Yan Zhuang , Boya Fu , Fei Liu
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