scholarly journals 4D Data Cubes from Radio-Interferometric Spectroscopic Snapshot Imaging

Solar Physics ◽  
2017 ◽  
Vol 292 (11) ◽  
Author(s):  
Atul Mohan ◽  
Divya Oberoi
Keyword(s):  
Author(s):  
E. E. Akimkina

The problems of structuring of indicators in multidimensional data cubes with their subsequent processing with the help of end-user tools providing multidimensional visualization and data management are analyzed; the possibilities of multidimensional data processing technologies for managing and supporting decision making at a design and technological enterprise are shown; practical recommendations on the use of domestic computer environments for the structuring and visualization of multidimensional data cubes are given.


2021 ◽  
Vol 258 ◽  
pp. 112364
Author(s):  
Han Liu ◽  
Peng Gong ◽  
Jie Wang ◽  
Xi Wang ◽  
Grant Ning ◽  
...  

1995 ◽  
Vol 12 (2) ◽  
pp. 227-238 ◽  
Author(s):  
A. M. Burgess ◽  
R. W. Hunstead

AbstractRadio snapshot imaging is an efficient observing method which allows several sources to be observed in the one session. Snapshot observing with the Australia Telescope Compact Array (ATCA) involves special difficulties, as the small number of antennas combined with the short total integration time leads to high sidelobe levels in the raw images. The images can be improved markedly by standard deconvolution techniques, but more care is required in their use because of the difficulty in distinguishing real emission from artefacts. This study, based on a set of snapshot observations of strong sources at 5 GHz, gives guidance on both the planning of observations and the data reduction. We show that snapshot imaging with the 6 km ATCA can achieve a dynamic range of 100–200:1 provided certain conditions are met, namely a peak flux density > 100 mJy, an angular size ≤ 30″ and an hour-angle coverage spanning at least six well-separated 5-minute cuts. When observing weak sources it is essential for calibration sources to be selected carefully and observed frequently.


2012 ◽  
Vol 29 (3) ◽  
pp. 244-250 ◽  
Author(s):  
L. Flöer ◽  
B. Winkel

AbstractToday, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline.


2000 ◽  
Vol 34 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Weifa Liang ◽  
Hui Wang ◽  
Maria E. Orlowska
Keyword(s):  

2021 ◽  
Vol 37 (3) ◽  
pp. 308
Author(s):  
Tarik De Melo e Silva Rocha ◽  
Rodrigo Rocha Silva ◽  
Tiago Garcia De Senna Carneiro ◽  
Joubert De Castro Lima
Keyword(s):  

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