On Board Data Compression: Distortion and Complexity Related Aspects (bibtex)
by Ahmed Nabil Belbachir, Horst Bischof
Abstract:
Digital signal Processing (DSP), and in particular data analysis and compression, has been studied for many years. However, only the recent advances in computing technology have made it possible to use DSP in day-to-day applications. Users expect the data to be transmitted in a minimum of time and to take up as little storage space as possible. These requirements call for efficient data compression algorithms in term of results quality and algorithmic complexity. The users want a good data quality with very fast compression and decompression as not to have to wait for data to be usable. Therefore, an accurate investigation on compression algorithms performances has to be performed. The performance of an algorithm can be analyzed using two criteria: the result quality i.e. high Signal-to-Noise Ratio vs Compression ratio and the algorithmic complexity. This report addresses both aspects of compression. In the first part of the report, noise influence on the compression method is stressed. The notion of algorithmic complexity is formalized using both approaches qualitative and quantitative in the second part of the report. In the third part, an new concept 'Integrated data compression' is introduced. In this part, we provide an optimization of On-board compression algorithm in terms of algorithm complexity and results quality, introducing a distributed exploitation of the data in both sides remote and user side. Application results of the method for the case study 'HERSCHEL/PACS Infrared Camera and Spectrometer' are presented in an other paper.
Reference:
On Board Data Compression: Distortion and Complexity Related Aspects (Ahmed Nabil Belbachir, Horst Bischof), Technical report, PRIP, TU Wien, 2003.
Bibtex Entry:
@TechReport{PTR-Belbachir03a,
  author =	 "Ahmed Nabil Belbachir and Horst Bischof",
  title =	 "On Board {D}ata {C}ompression: {D}istortion and
                  {C}omplexity {R}elated {A}spects",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-075",
  year =	 "2003",
  url =		 "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr75.pdf",
  abstract =	 "Digital signal Processing (DSP), and in particular
                  data analysis and compression, has been studied for
                  many years. However, only the recent advances in
                  computing technology have made it possible to use
                  DSP in day-to-day applications. Users expect the
                  data to be transmitted in a minimum of time and to
                  take up as little storage space as possible. These
                  requirements call for efficient data compression
                  algorithms in term of results quality and
                  algorithmic complexity. The users want a good data
                  quality with very fast compression and decompression
                  as not to have to wait for data to be
                  usable. Therefore, an accurate investigation on
                  compression algorithms performances has to be
                  performed. The performance of an algorithm can be
                  analyzed using two criteria: the result quality
                  i.e. high Signal-to-Noise Ratio vs Compression ratio
                  and the algorithmic complexity. This report
                  addresses both aspects of compression. In the first
                  part of the report, noise influence on the
                  compression method is stressed. The notion of
                  algorithmic complexity is formalized using both
                  approaches qualitative and quantitative in the
                  second part of the report. In the third part, an new
                  concept 'Integrated data compression' is
                  introduced. In this part, we provide an optimization
                  of On-board compression algorithm in terms of
                  algorithm complexity and results quality,
                  introducing a distributed exploitation of the data
                  in both sides remote and user side. Application
                  results of the method for the case study
                  'HERSCHEL/PACS Infrared Camera and Spectrometer' are
                  presented in an other paper.",
}
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