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Adaptive interpolation algorithm for hierarchical image compression

M.V. Gashnikov1,2, N.I. Glumov1,2, V.V. Sergeev1,2

1 IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS,
443001, Samara, Russia, Molodogvardeyskaya 151,
2 Samara National Research University, 443086, Samara, Russia, Moskovskoye Shosse 34

 PDF, 397 kB

Pages: 89-93.

Full text of article: Russian language.

Abstract:
The paper proposes a new adaptive interpolation algorithm for hierarchical image compression. The algorithm is based on the use of a parameterized decision rule, which is adjusted for each particular image during its processing. The developed interpolation algorithm is compared with the existing ones.

Keywords:
adaptive interpolation algorithm, image compression, parameterized decision rule, image processing.

Citation:
Gashnikov MV, Glumov NI, Sergeyev VV. Adaptive interpolation algorithm for hierarchical image compression. Computer optics 2002; 23: 89-93.

References:
  1. Alexandrov RV, Gorsky ID. Image representation and processing: a recursive approach. Dordrecht: Springer Science+Business Media; 1993.
  2. Kortman CM. Redundancy reduction – A practical method of data compression. Proc IEEE 1967; 55(3): 253-263.
  3. Vasin YG, Bakareva VP. Recurrent algorithms for adaptive compression using well-adapted local restoration functions [In Russian]. In Book: CAD software: Interuniversity collection of papers. Vol I. Gorky: GSU Publisher; 1978: 13.
  4. Efimov VM, Kolesnikov AN. Effectiveness estimation of the hierarchical and line-by-line lossless compression algorithms [In Russian]. Proc 3rd All-Russian Conference “Pattern Recognition and Image Analysis: New Information Technologies” 1997; I: 157-161.
  5. Gashnikov MV, Glumov NI, Sergeev VV. Information technology for image compression in online remote sensing systems. Izvestia of Samara Scientific Center of the Russian Academy of Sciences 1999; 1: 99-107.
  6. Gashnikov M, Glumov N, Sergeyev V. Compression method for real-time systems of remote sensing. Proc 15th Int Conf on Pattern Recognition 2000; 3: 232-235.

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