Skip to main content

On the Efficiency of Luminance-Based Palette Reordering of Color-Quantized Images

  • Conference paper
  • First Online:
Pattern Recognition and Image Analysis (IbPRIA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2652))

Included in the following conference series:

  • 680 Accesses

Abstract

Luminance-based palette reordering is often considered less efficient than other more complex approaches, in what concerns improving the compression of color-indexed images. In this paper, we provide experimental evidence that, for color-quantized natural images, this may not be always the case. In fact, we show that, for dithered images with 128 colors or more, luminance-based reordering outperforms other more complex methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Welch, T.A.: A technique for high-performance data compression. IEEE Computer 17(6), 8–19 (1984)

    Article  Google Scholar 

  2. Ziv, J., Lempel, A.: Compression of individual sequences via variable-rate coding. IEEE Trans. on Information Theory 24(5), 530–536 (1978)

    Article  MathSciNet  Google Scholar 

  3. Ausbeck Jr., P.J.: The piecewise-constant image model. Proceedings of the IEEE 88(11), 1779–1789 (2000)

    Article  Google Scholar 

  4. Yoo, Y., Kwon, Y.G., Ortega, A.: Embedded image-domain compression using context models. In: Proc. of the 6th IEEE Int. Conf. on Image Processing, ICIP 1999, Kobe, Japan, vol. I, pp. 477–481 (1999)

    Google Scholar 

  5. Ratnakar, V.: RAPP: Lossless image compression with runs of adaptive pixel patterns. In: Proc. of the 32nd Asilomar Conf. on Signals, Systems, and Computers, vol. 2, pp. 1251–1255 (1998)

    Google Scholar 

  6. Chen, X., Kwong, S., Feng, J.-F.: A new compression scheme for color-quantized images. IEEE Trans. on Circuits and Systems for Video Technology 12(10), 904–908 (2002)

    Article  Google Scholar 

  7. ISO/IEC 14495–1 and ITU Recommendation T.87, Information technology - Lossless and near-lossless compression of continuous-tone still images (1999)

    Google Scholar 

  8. Weinberger, M.J., Seroussi, G., Sapiro, G.: The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS. IEEE Trans. on Image Processing 9(8), 1309–1324 (2000)

    Article  Google Scholar 

  9. ISO/IEC International Standard 15444–1, ITU-T Recommendation T.800, Information technology - JPEG 2000 image coding system (2000)

    Google Scholar 

  10. Skodras, A., Christopoulos, C., Ebrahimi, T.: The JPEG 2000 still image compression standard. IEEE Signal Processing Magazine 18(5), 36–58 (2001)

    Article  Google Scholar 

  11. Memon, N.D., Venkateswaran, A.: On ordering color maps for lossless predictive coding. IEEE Trans. on Image Processing 5(5), 1522–1527 (1996)

    Article  Google Scholar 

  12. Battiato, S., Gallo, G., Impoco, G., Stanco, F.: A color reindexing algorithm for lossless compression of digital images. In: Proc. of the IEEE Spring Conf. on Computer Graphics, Budmerice, Slovakia, pp. 104–108 (2001)

    Google Scholar 

  13. Spira, A., Malah, D.: Improved lossless compression of color-mapped images by an approximate solution of the traveling salesman problem. In: Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP-2001, Salt Lake City, UT, vol. III, pp. 1797–1800 (2001)

    Google Scholar 

  14. Zeng, W., Li, J., Lei, S.: An efficient color re-indexing scheme for palette-based compression. In: Proc. of the 7th IEEE Int. Conf. on Image Processing, ICIP- 2000, Vancouver, Canada, vol. III, pp. 476–479 (2000)

    Google Scholar 

  15. Zaccarin, A., Liu, B.: A novel approach for coding color quantized images. IEEE Trans. on Image Processing 2(4), 442–453 (1993)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pinho, A.J., Neves, A.J.R. (2003). On the Efficiency of Luminance-Based Palette Reordering of Color-Quantized Images. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_89

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-44871-6_89

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40217-6

  • Online ISBN: 978-3-540-44871-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics