scholarly journals Point spread function modelling for wide-field small-aperture telescopes with a denoising autoencoder

2020 ◽  
Vol 493 (1) ◽  
pp. 651-660 ◽  
Author(s):  
Peng Jia ◽  
Xiyu Li ◽  
Zhengyang Li ◽  
Weinan Wang ◽  
Dongmei Cai
Keyword(s):  
Point Spread Function ◽  
Wide Field ◽  
Calibration Data ◽  
Post Processing ◽  
Denoising Autoencoder ◽  
Small Aperture ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling ◽  
Star Images

ABSTRACT The point spread function reflects the state of an optical telescope and it is important for the design of data post-processing methods. For wide-field small-aperture telescopes, the point spread function is hard to model because it is affected by many different effects and has strong temporal and spatial variations. In this paper, we propose the use of a denoising autoencoder, a type of deep neural network, to model the point spread function of wide-field small-aperture telescopes. The denoising autoencoder is a point spread function modelling method, based on pure data, which uses calibration data from real observations or numerical simulated results as point spread function templates. According to real observation conditions, different levels of random noise or aberrations are added to point spread function templates, making them realizations of the point spread function (i.e. simulated star images). Then we train the denoising autoencoder with realizations and templates of the point spread function. After training, the denoising autoencoder learns the manifold space of the point spread function and it can map any star images obtained by wide-field small-aperture telescopes directly to its point spread function. This could be used to design data post-processing or optical system alignment methods.

Improving position accuracy for telescopes with small aperture and wide field of view utilizing point spread function modelling

2020 ◽  
Vol 497 (3) ◽  
pp. 4000-4008
Author(s):  
Rongyu Sun ◽  
Shengxian Yu ◽  
Peng Jia ◽  
Changyin Zhao
Keyword(s):  
Point Spread Function ◽  
Large Scale ◽  
Field Of View ◽  
Wide Field ◽  
Position Measurement ◽  
Small Aperture ◽  
Position Accuracy ◽  
Point Spread ◽  
Wide Field Of View ◽  
Spread Function

ABSTRACT Telescopes with a small aperture and a wide field of view are widely used and play a significant role in large-scale state-of-the-art sky survey applications, such as transient detection and near-Earth object observations. However, owing to the specific defects caused by optical aberrations, the image quality and efficiency of source detection are affected. To achieve high-accuracy position measurements, an innovative technique is proposed. First, a large number of raw images are analysed using principal component analysis. Then, the effective point spread function is reconstructed, which reflects the state of the telescope and reveals the characteristics of the imaging process. Finally, based on the point spread function model, the centroids of star images are estimated iteratively. To test the efficiency and reliability of our algorithm, a large number of simulated images are produced, and a telescope with small aperture and wide field of view is utilized to acquire the raw images. The position measurement of sources is performed using our novel method and two other common methods on these data. Based on a comparison of the results, the improvement is investigated, and it is demonstrated that our proposed technique outperforms the others on position accuracy. We explore the limitations and potential gains that may be achieved by applying this technique to custom systems designed specifically for wide-field astronomical applications.

scholarly journals Surface Brightness Profiles of 68 Globular Clusters Derived From Electronic Camera Recordings

1980 ◽  
Vol 85 ◽  
pp. 459-460
Author(s):  
Gerald E. Kron ◽  
Katherine C. Gordon ◽  
Anthony V. Hewitt
Keyword(s):  
Point Spread Function ◽  
Globular Clusters ◽  
Surface Brightness ◽  
Naval Observatory ◽  
Point Spread ◽  
Spread Function ◽  
Spacial Information ◽  
Cluster Profiles ◽  
Star Images ◽  
The U.S

Images of 68 globular clusters have been recorded in 125 exposures made with the electronic camera of the U.S. Naval Observatory on the 24-inch, 40-inch and 61-inch reflecting telescopes at the Flagstaff Station. The images were electronically malfocussed to allow the integration of light from the fainter cluster stars without saturation of the central portions of the brighter star images. Spacial information thus lost was partly regained by subsequent linear deconvolution of the cluster profiles by means of a star profile used as the point spread function.

Brain PET imaging optimization with time of flight and point spread function modelling

2015 ◽  
Vol 31 (8) ◽  
pp. 948-955 ◽  
Author(s):  
Elena Prieto ◽  
Josep M. Martí-Climent ◽  
Verónica Morán ◽  
Lidia Sancho ◽  
Benigno Barbés ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Point Spread Function ◽  
Time Of Flight ◽  
Brain Pet ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling

scholarly journals On point spread function modelling: towards optimal interpolation

2011 ◽  
Vol 419 (3) ◽  
pp. 2356-2368 ◽  
Author(s):  
Joel Bergé ◽  
Sedona Price ◽  
Adam Amara ◽  
Jason Rhodes
Keyword(s):  
Point Spread Function ◽  
Optimal Interpolation ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling

scholarly journals Variability and transient search in the SUDARE–VOICE field: a new method to extract the light curves

2020 ◽  
Vol 493 (3) ◽  
pp. 3825-3837
Author(s):  
Dezi Liu ◽  
Wenqiang Deng ◽  
Zuhui Fan ◽  
Liping Fu ◽  
Giovanni Covone ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Point Spread Function ◽  
Forthcoming Paper ◽  
Light Curves ◽  
New Method ◽  
Imaging Data ◽  
Point Spread ◽  
Spread Function ◽  
Function Modelling ◽  
The Difference

ABSTRACT The VLT Survey Telescope (VST) Optical Imaging of the CDFS and ES1 Fields Survey, in synergy with the SUDARE survey, is a deep optical ugri imaging of the CDFS and ES1 fields using the VST. The observations for the CDFS field comprise about 4.38 deg2 down to r ∼ 26 mag. The total on-sky time spans over 4 yr in this field, distributed over four adjacent sub-fields. In this paper, we use the multiepoch r-band imaging data to measure the variability of the detected objects and search for transients. We perform careful astrometric and photometric calibrations and point spread function modelling. A new method, referring to as differential running-average photometry, is proposed to measure the light curves of the detected objects. With the method, the difference of PSFs between different epochs can be reduced, and the background fluctuations are also suppressed. Detailed uncertainty analysis and detrending corrections on the light curves are performed. We visually inspect the light curves to select variable objects, and present some objects with interesting light curves. Further investigation of these objects in combination with multiband data will be presented in our forthcoming paper.

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