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McNerney, P. 2000, in ASP Conf. Ser., Vol. 216, Astronomical Data
Analysis Software and Systems IX, eds. N. Manset, C. Veillet, D. Crabtree (San Francisco: ASP), 323
The Communication of Images from New Generation Astronomical
Telescopes
P. McNerney
Astrophysics Research Institute,
Liverpool John Moores University,
Birkenhead,
Merseyside CH41 1LD,
UK
Abstract:
New Generation Astronomical Telescopes (NGAT), a class of telescopes
designed to be operated remotely and robotically, require efficient
methods for communicating images over heterogeneous and low-bandwidth
data networks such as the Internet. NGATs enable the allocation of time
on a telescope to a diverse range of users having differing
requirements. To satisfy these needs, research into novel ways of
compressing astronomical images has been undertaken. Methods researched
thus far involve the classification of astronomical images based on
object parameterisation, progressive image transmission, and evaluation
of existing image compression schemes. The methods being developed
target the needs of users that include astronomers, schools and
colleges, and Public Understanding of Science and Technology (PUST)
displays.
The Astrophysics Research Institute (ARI) and the Electronic Design And
Manufacturing (EDAM) Centre of Liverpool John Moores University (JMU),
in collaboration with dB Research Limited have set out to design
leading-edge hardware and software for the purpose of acquiring,
communicating and processing astronomical images from the New Generation
Astronomical Telescope (NGAT).
The aim is to develop the means, in software, to efficiently
communicate, process and display images generated by the telescope for a
diverse audience that includes professional astronomers, schools and
colleges, and the general public visiting a planetarium. The members of
this audience have different needs and expectations of the images
acquired by the telescope. The communication system must take into
account and cater for these.
The New Generation Astronomical Telescope (NGAT) is to be a fully
automated robotic telescope. The Liverpool Telescope (LT) will be the
first NGAT and will be the demonstration unit for the technology being
developed. The LT is to be sited on a mountain top at La Palma in the
Canary Isles and controlled from the ARI.
The NGAT will be controlled and operated via the Internet, enabling
remote operation by researchers and astronomers, and promoting the
Public Understanding of Science and Technology (PUST). Schools, colleges
and planetariums will be given time on the telescope, during which they
will be able to remotely position and capture images from it. Images
will be acquired using a 2048x2048 pixel 16-bit CCD. To preserve the
large dynamic range of the CCD, the read-out has to take place at a
relatively low data rate of 100-150kB/second or less. At these
rates, it would take 55-80 seconds to completely read out the contents
of the CCD. For public displays this is unaceptably long, and a lower
SNR may have to be tolerated.
An investigation of communications links (Thoma & Long 1997) was
undertaken throughout 1998 to ascertain the necessary level of
compression required in both average and worst case conditions. The
investigation utilised ftp to perform unattended retrieval of
three test files, once per hour, from ing.iac.es on La Palma to a JANET
Starlink node at JMU in the UK.
An appraisal of existing lossy compression schemes was done to determine
how they perform at high compression ratios (
80:1). Figure 1
compares the effects of block-DCT and fractal compression with
compression based on wavelets (Rioul & Vetterli 1991). Blocking
artefacts are very noticeable for the DCT encoded image and the fractal
encoded image. It was found that wavelet-based compression schemes
produce visibly better images at high compression ratios.
Figure 1:
Comparison of existing image compression schemes.
 |
Photometric accuracy needs to be preserved only for images of stellar
fields and extended sources. Therefore, different compression schemes
can be applied for images of planets, etc., where visible structure is
important rather than intensity profiles.
Image classification can be achieved by analysing the profile and
features of the image histogram. Stellar fields and galaxies are
classified as type 0; planets and surfaces are classified as type 1. The
classifications are determined by analysing the histogram with respect
to a parabola and gradients of vectors that are a function of histogram
bins intersecting the parabola.
Methods typically used by software developed to highly compress
astronomical images, e.g. Hcompress (White 1992), have been based on
wavelet transforms. These perform well at retaining photometric
accuracy, but suffer from the introduction of visible artefacts in the
sky background, and error in the detected position of sources. This is
illustrated by (b) and (c) of Figure 2, square-rooted images of a
stellar field. Figure 2 (d) is the result of applying a new method based
on thresholding and run-length encoding that aims to model the sky
background so that only pixels above a threshold, calculated from the
image median, need to be transmitted. The LT requirement is for
compressed images to be 
30 kB. By applying a suitable
loss-less encoding method (Nelson 1996) after thresholded RLE, a
1024x1024 16 bits/pixel FITS image of a stellar field can be compressed
to 
25kB. An extension of this method allows progressive
transmission of the image by decomposing it into layers.
Figure 2:
Comparison of astronomical image compression schemes.
 |
Acknowledgments
I thank my supervisors; Dr Iain Steele and Dr David Harvey of JMU, and Prof Bill Mullarkey of dB Research Ltd, for their guidance.
References
Nelson, R. 1996, Dr. Dobb's Journal, September, 46
Rioul, O. & Vetterli, M. 1991, IEEE Signal Processing
Magazine, October, 14
Thoma, G. R. & Long, L. R. 1997, IEEE Multimedia, April-June, 36
White, R. L. 1992, Proc. of the NASA Space and Earth Sciences Data Compression Workshop, ed. James C. Tilton, March
© Copyright 2000 Astronomical Society of the Pacific, 390 Ashton Avenue, San Francisco, California 94112, USA
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