Hierarchical compression for hyperspectral image storage
M.V. Gashnikov, N.I. Glumov

Image Processing Systems Institute, Russian Academy of Sciences,
Samara State Aerospace University

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Full text of article: Russian language.

DOI: 10.18287/0134-2452-2014-38-3-482-488

Pages: 482-488.

Abstract:
We investigate the possibility of using of hierarchical storage compression for problem of hyperspectral images storage. Results of image analysis of SpecTIR and AVIRIS spectrometers shown. Approximation of the spectral channels is proposed to improve the efficiency of the method while still allowing access to individual components. Computational experiments to study the efficiency of the developed algorithms on 16-bit hyperspectral images implemented.

Key words:
image compression, hyperspectral images storage, control of maximum deviation, hierarchical grid interpolation.

References:

  1. Borengasser, M. Hyperspectral Remote Sensing – Principles and Applications / M. Borengasser [et al]. – CRC Press, 2004. – 128 p.
  2. SpecTIR Data – Advanced Hyperspectral and Geospatial Solutions / Corporate Headquarters SpecTIR Remote Sensing Division // http://www.spectir.com/free-data-samples.
  3. AVIRIS Data – Ordering Free AVIRIS Standard Data Products / Jet Propulsion Laboratory // http://aviris.jpl.na­sa.gov/data/free_data.html.
  4. Gashnikov, M.V. Hierarchical grid interpolation for hyperspectral image compression / M.V. Gashnikov, N.I. Glumov // Computer Optics. – 2014. – V. 38(1). – P. 87-93.
  5. Sergeev, V.V. A hierarchical compression method for space images / M.V. Gashnikov, N.I. Glumov, V.V. Sergeev // Automation and Remote Control. – 2010. – V. 71(3). – P. 501-513.
  6. Gashnikov, M.V. Preparing a Common Raster Coverage for a Territory Based on Hierarchical Compressed Presentation of Orthoimages / M.V. Gashnikov, N.I. Glumov, A.V. Chernov // Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications. – 2009. – V. 19, Issue 1. – P. 39-42.
  7. Gashnikov, M.V. Hierarchical compression of the multidimansional data in the regional bank of samara region satellite images / M.V. Gashnikov, N.I. Glumov // Proceedings of 9-th International Conference on Pattern Recognition and Image Analysis: New Information Technologies (PRIA-9-2008). – Russian Federation, Nizhni Novgorod, September 15-19, 2008. – V. 1. – P. 159-161.
  8. Wallace, G. The JPEG Still Picture Compression Standard / G. Wallace // Communications of the ACM. – 1991. – V. 34, Issue 4. – P. 30-44.
  9. Computer Image Processing, Part II: Methods and algorithms / A.V. Chernov, V.M. Chernov, M.A. Chicheva, V.A. Fursov, M.V. Gash­nikov, N.I. Glumov, N.Yu. Ilyaso­va, A.G. Khra­mov, A.O. Korepanov, A.V. Kupriyanov, E.V. Myasnikov, V.V. Myas­nikov, S.B. Popov, V.V. Sergeyev, V.A. Soifer. – VDM Verlag, 2009. – 584 p.
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