Skip to main content

Lossy Compression of Images with Additive Noise

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3708))

Abstract

Lossy compression of noise-free and noisy images differs from each other. While in the first case image quality is decreasing with an increase of compression ratio, in the second case coding image quality evaluated with respect to a noise-free image can be improved for some range of compression ratios. This paper is devoted to the problem of lossy compression of noisy images that can take place, e.g., in compression of remote sensing data. The efficiency of several approaches to this problem is studied. Image pre-filtering is shown to be expedient for coded image quality improvement and/or increase of compression ratio. Some recommendations on how to set the compression ratio to provide quasioptimal quality of coded images are given. A novel DCT-based image compression method is briefly described and its performance is compared to JPEG and JPEG2000 with application to lossy noisy image coding.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Salomon, D.: Data Compression. The Complete Reference, 3rd edn. Springer, Heidelberg (2004)

    MATH  Google Scholar 

  2. Wei, D., Odegard, J.E., Guo, H., Lang, M., Burrus, C.S.: Simultaneous Noise Reduction and SAR Image Data Compression Using Best Wavelet Packet Basis. In: Proceedings of International Conference on Image Processing, vol. 3, pp. 200–203 (1995)

    Google Scholar 

  3. Mittal, M.L., Singh, V.K., Krishnan, R.: Wavelet Transform Based Technique for Speckle Noise Suppression and Data Compression for SAR Images. In: Proceedings of the Fifth International Symposium on Signal Processing and Applications, pp. 781–784 (1999)

    Google Scholar 

  4. Chan, T.C.L., Hsung, T.C., Lun, D.P.K.: Improved MPEG-4 Still Texture Image Coding under Noisy Environment. IEEE Transactions on Image Processing 12(5), 500–508 (2003)

    Article  MathSciNet  Google Scholar 

  5. Kim, S.D., Jang, S.K., Kim, M.J., Ra, J.B.: Efficient Block-based Coding of Noisy Images by Combined Pre-filtering and DCT. Electronic Letters 35(20), 1717–1719 (1999)

    Article  Google Scholar 

  6. Al-Shaykh, O.K., Mersereau, R.M.: Lossy Compression of Noisy Images. IEEE Transactions on Image Processing 7(12), 1641–1652 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  7. Al-Shaykh, O.K., Mersereau, R.M.: Restoration of Lossy Compressed Noisy Images. IEEE Transactions on Image Processing 8(10), 1348–1360 (1999)

    Article  Google Scholar 

  8. Sabelkin, M.V., Ponomarenko, N.N.: MM-Band Radar Image Wavelet Compression with Prefiltering. In: Proceedings of Kharkov Symposium on Millimeter and Sub-millimeter Waves MSMW, vol. 1, pp. 280–282 (2001)

    Google Scholar 

  9. Chang, S.G., Yu, B., Vetterli, M.: Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. on Image Processing 9(9), 1532–1546 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  10. Venkatraman, M., Kwon, H., Nasrabadi, N.M.: Object-Based SAR Image Compression Using Vector Quantization. IEEE Trans. on Aerospace and Electronic Systems AES-36(4), 1036–1046 (2000)

    Google Scholar 

  11. Koh, S.S., Kim, C.H.: Fractal Image Coding Based on the Accurate Estimation of Image Parameters from Noise Image. In: Proceedings of IEEE International Conference on Multimedia and Expo, pp. 1159–1162 (2001)

    Google Scholar 

  12. Ponomarenko, N.N., Lukin, V.V., Egiazarian, K.O., Astola, J.T.: DCT Based High Quality Image Compression. In: Scandinavian Conference on Image Analysis (2005) (accepted )

    Google Scholar 

  13. Egiazarian, K., Helsingius, M., Kuosmanen, P., Astola, J.: Removal of blocking and ringing artifacts using transform domain denoising. In: Proc. of ISCAS 1999, vol. 4, pp. 139–142 (1999)

    Google Scholar 

  14. Egiazarian, K., Melnik, V., Lukin, V., Astola, J.: Local transform-based denoising for radar image processing. In: Proc. SPIE Nonlinear Image Processing and Pattern Analysis XII, vol. 4304, pp. 170–178 (2001)

    Google Scholar 

  15. Ponomarenko, N.N., Lukin, V.V., Abramov, S.K., Egiazarian, K.O., Astola, J.T.: Blind evaluation of additive noise variance in textured images by nonlinear processing of block DCT coefficients. In: Proc. of IS&T/SPIE International Conference on Image Processing: Algorithms and Systems, SPIE, vol. 5014, pp. 178–189 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ponomarenko, N., Lukin, V., Zriakhov, M., Egiazarian, K., Astola, J. (2005). Lossy Compression of Images with Additive Noise. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_48

Download citation

  • DOI: https://doi.org/10.1007/11558484_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29032-2

  • Online ISBN: 978-3-540-32046-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics