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Compression algorithms for multibeam sonar records

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Operational requirements of multibeam sonar systems result in very large volumes of datasets stored on local hard drives of operator's station. In this context, the process of archiving acquired data becomes a crucial problem. The paper investigates various lossy and lossless compression methods that can be applied to multibeam sonar data to reduce the size of acquired files without loosing relevant information. The specific character of MBS data allows applying various signal, image and video compression methods to achieve better results than when using standard compression tools. Various techniques of reordering the data were analyzed to achieve best possible compression ratio.
Czasopismo
Rocznik
Tom
Strony
55--62
Opis fizyczny
Bibliogr. 12 poz., rys., tab.
Twórcy
autor
Bibliografia
  • 1. E. Hammerstad, “Advanced multibeam echosounder technology,” Sea Technology, vol. 36, pp. 67-69,1995.
  • 2. B. Buelens, R. Williams, A. Saley, T. Pauly, “Model Inversion for Midwater Multibeam Backscatter Data Analysis”, Oceans - Europe 2005
  • 3. B. Buelens, R. Williams, A. Sale, T. Pauly “Midwater acoustic modeling for multibeam sonar simulation”
  • 4. Data Format Definition, Seabat 7k Data Format , Volume I. Version 0.54
  • 5. K. Karadimitriou, “Set Redundancy, the Enhanced Compression Model, and Methods for Compressing Sets of Similar Images”, Ph.D. Dissertation, Louisiana State University, Baton Rouge, LA, August 1996.
  • 6. http://reson.com
  • 7. K. Karadimitriou, M. Fenstermacher “Image Compression In Medical Image Databases Using Set Redundancy”, Division of Diagnostic Imaging, M.D. Anderson Cancer Center, Houston, TX
  • 8. Antaneus Feldspar, “An Explanation of the Deflate Algorithm”, http://zlib.net/
  • 9. Atsuro Ichigaya, Masaaki Kurozumi, Naohiro Hara, Yukihiro Nishida, and Eisuke Nakasu , “A Method of Estimating Coding PSNR Using Quantized DCT Coefficients”, IEEE Transactions on circuits and systems for video technology, vol. 16, no. 2, Februrary 2006
  • 10. Tommy C. L. Chan, Tai-Chiu Hsung, Member, IEEE, and Daniel Pak-Kong Lun, Member, IEEE, “Improved MPEG-4 Still Texture Image Coding Under Noisy Environment” IEEE transactions on image processing, vol. 12, no. 5, May 2003
  • 11. Qian Du, Member, IEEE, and Chein-I Chang, Senior Member, IEEE, “Linear Mixture Analysis-Based Compression for Hyperspectal Image Analysis”, IEEE Transactions on Geoscience and remote sensing, vol 42, no. 4, April 2004
  • 12. R. A. Schowengerdt, “Remote Sensing: Models and Methods for Image Processing”, 2nd ed. Orlando, FL: Academic, 1997, pp. 470–471.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWMA-0018-0007
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