Skip to main content

Advertisement

JPEG2000 Compatible Lossless Coding of Floating-Point Data

Article metrics

  • 1235 Accesses

  • 2 Citations

Abstract

Many scientific applications require that image data be stored in floating-point format due to the large dynamic range of the data. These applications pose a problem if the data needs to be compressed since modern image compression standards, such as JPEG2000, are only defined to operate on fixed-point or integer data. This paper proposes straightforward extensions to the JPEG2000 image compression standard which allow for the efficient coding of floating-point data. These extensions maintain desirable properties of JPEG2000, such as lossless and rate distortion optimal lossy decompression from the same coded bit stream, scalable embedded bit streams, error resilience, and implementation on low-memory hardware. Although the proposed methods can be used for both lossy and lossless compression, the discussion in this paper focuses on, and the test results are limited to, the lossless case. Test results on real image data show that the proposed lossless methods have raw compression performance that is competitive with, and sometime exceeds, current state-of-the-art methods.

[12345678910111213]

References

  1. 1.

    Sayood K: Introduction to Data Compression. Morgan Kaufmann, San Francisco, Calif, USA; 2000.

  2. 2.

    Gersho A, Gray R: Vector Quantization and Signal Compression. Kluwer Academic, Norwell, Mass, USA; 1992.

  3. 3.

    Taubman D, Marcellin M: JPEG2000: Image Compression Fundamentals, Standards, and Practice. Kluwer Academic, Boston, Mass, USA; 2002.

  4. 4.

    Engelson V, Fritzson D, Fritzson P: Lossless compression of high-volume numerical data from simulations. Proceedings of Data Compression Conference (DDC '00), March 2000, Snowbird, Utah, USA 574.

  5. 5.

    Ghido F: An efficient algorithm for lossless compression of IEEE float audio. Proceedings of Data Compression Conference (DDC '04), March 2004, Snowbird, Utah, USA 429-438.

  6. 6.

    Ratanaworabhan P, Jian K, Burtscher M: Fast lossless compression of scientific floating-point data. Proceedings of Data Compression Conference (DCC '06), March 2006, Snowbird, Utah, USA 133-142.

  7. 7.

    Lindstrom P, Isenburg M: Fast and efficient compression of floating-point data. IEEE Transactions on Visualization and Computer Graphics 2006,12(5):1245-1250. 10.1109/TVCG.2006.143

  8. 8.

    T. Instruments : TMS320C3x User's Guide. Texas Instruments, 1994

  9. 9.

    Mallat SG: A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 1989,11(7):674-693. 10.1109/34.192463

  10. 10.

    Usevitch BE: A tutorial on modern lossy wavelet image compression: foundations of JPEG 2000. IEEE Signal Processing Magazine 2001,18(5):22-35. 10.1109/79.952803

  11. 11.

    Adams M: The JasPer Project. Source code and user manuals, http://www.ece.uvic.ca/~mdadams/jasper/

  12. 12.

    http://vis.computer.org/vis2004contest/data.html

  13. 13.

    Kosheleva OM, Usevitch BE, Cabrera SD, Vidal E Jr.: Rate distortion optimal bit allocation methods for volumetric data using JPEG 2000. IEEE Transactions on Image Processing 2006,15(8):2106-2112. 10.1109/TIP.2006.875216

Download references

Author information

Correspondence to BryanE Usevitch.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Keywords

  • Real Image
  • Rate Distortion
  • Compression Performance
  • Large Dynamic Range
  • Modern Image