Abstract

This paper deals with a compression of image data in applications in astronomy. Astronomical images have typical specific properties — high grayscale bit depth, size, noise occurrence and special processing algorithms. They belong to the class of scientific images. Their processing and compression is quite different from the classical approach of multimedia image processing. The database of images from BOOTES (Burst Observer and Optical Transient Exploring System) has been chosen as a source of the testing signal. BOOTES is a Czech-Spanish robotic telescope for observing AGN (active galactic nuclei) and the optical transient of GRB (gamma ray bursts) searching. This paper discusses an approach based on an analysis of statistical properties of image data. A comparison of two irrelevancy reduction methods is presented from a scientific (astrometric and photometric) point of view. The first method is based on a statistical approach, using the Karhunen-Loeve transform (KLT) with uniform quantization in the spectral domain. The second technique is derived from wavelet decomposition with adaptive selection of used prediction coefficients. Finally, the comparison of three redundancy reduction methods is discussed. Multimedia format JPEG2000 and HCOMPRESS, designed especially for astronomical images, are compared with the new Astronomical Context Coder (ACC) coder based on adaptive median regression.

Highlights

  • This paper deals with scientific image data compression

  • The data for analysis was collected during work on the international (Czech-Spanish-Italian) BOOTES experiment (Burst Observer Optical Transient Exploring System) [2]

  • BOOTES has been in service since 1998 as the first Spanish robotic telescope for sky observation [4]

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Summary

Introduction

This paper deals with scientific image data compression. The data for analysis was collected during work on the international (Czech-Spanish-Italian) BOOTES experiment (Burst Observer Optical Transient Exploring System) [2]. BOOTES has been in service since 1998 as the first Spanish robotic telescope for sky observation [4]. This system is one of three similar systems in full operation in the world, and has three main stations. The best way to guarantee maximally accurate and reliable results from post-processing an astronomical image is to preserve the image without any change or loss of information. For this reason lossless compression techniques are often preferred in this area

Astronomical images
JPEG2000
HCOMPRESS
CCSDS-LDC or Rice algorithm
ACC Coder
Achievable compression ratios
Lossy astronomical image compression
Distortion measurement of lossy coders
Conclusion
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