TELECOMMUNICATIONS AND RADIO ENGINEERING - 2011 Vol. 70,
No 15 		 

 

 

 

ADAPTIVE JPEG LOSSY COMPRESSION OF COLOR IMAGES



N.N. Ponomarenko1, V.V. Lukin1, K.O. Egiazarian2, & L. Lepisto3
1Dept 504, National Aerospace University,
17 Chkalova Street, Kharkiv, 61070, Ukraine
2Tampere International Center for Signal Processing,
Tampere University of Technology P.O.Box-553, FIN-33101, Tampere, Finland
3 Nokia Corporation, Visiokatu 3, FI-33720 Tampere, Finland
Address all correspondence to V.V. Lukin E-mail: lukin@ai.kharkov.com

Abstract
JPEG based compression of color digital images in visually lossless manner with adaptation to image/distortion characteristics and providing appropriately large compression ratio is considered. Adaptation is performed for raw images with taking into account further nonlinear transformations carried out in imaging devices as digital cameras before compression. Blur and noise parameters are estimated and/or predicted and they serve for setting a proper quantization table for JPEG compression. The proposed approach is tested for a large number of real life color photos. It is demonstrated that compression ratio can be on the average increased by about two times compared to super-high quality (SHQ) mode used in modern digital cameras. No visible differences are observed between images compressed by adaptive JPEG and in SHQ mode.
KEY WORDS:adaptive compression, color images

References

  1. Salomon, D., (2004), Data Compression: The Complete Reference. Berlin: Springer-Verlag.
  2. Wallace, G.K., (1991), The JPEG Still Picture Compression Standard. Comm. of the ACM, 34(4).
  3. Pennebaker, W.B. and Mitchell, J.L., (1993), JPEG Still Image Data Compression Standard, Van Nostrand Reinhold, New York.
  4. Christopoulos, C., Skodras, A., and Ebrahimi, T., (2000), The JPEG2000 still image coding system: an overview, IEEE Trans. on Consumer Electronics, 46(4):1103-1127.
  5. Slone, R.M. et al., (2000), Assessment of visually lossless irreversible image compression: comparison of three methods by using an image comparison workstation, Radiology, 217:772-779.
  6. Theuwissen, A.J.P., (2004), Image Processing Chain in Digital Still Cameras, Digest of Symposium on VLSI Circuits, pp. 2-5.
  7. Foi, A., Alenius, S., Trimeche, M., Katkovnik, V., and Egiazarian, K., (2005), A Spatially Adaptive Poissonian Image Deblurring, Proceedings of ICIP, 2:925-928.
  8. Paliy, D., Foi, A., Bilcu, R., and Katkovnik, V., (2008), Denoising and Interpolation of Noisy Bayer Data with Adaptive Cross-Color Filters, Proceedings of SPIE-IS&T Electronic Imaging, Visual Comm. Image Proc., Vol. 6822.    
  9. Ponomarenko, N., Krivenko, S., Lukin, V., Egiazarian, K., and Astola, J., (2010), Lossy Compression of Noisy Images Based on Visual Quality: a Comprehensive Study, EURASIP Journal on Advances in Signal Processing, Article ID 976436, 13 pages (http://www.hindawi.com/journals/asp/2010/976436.html).
  10. Ponomarenko, N., Krivenko, S., Lukin, V., and Egiazarian, K., (2009), Visual Quality of Lossy Compressed Images, Proceedings of CADSM2009, pp. 137-142.
  11. Ponomarenko, N., Silvestri, F., Egiazarian, K., Carli, M., Astola, J., and Lukin, V., (2007), On between-coefficient contrast masking of DCT basis functions, CD-ROM Proceedings of VPQM, 4 p.
  12. Kurimo, E., Lepisto, L., Nikkanen, J., Gren, J., Kunttu, I., and Laaksonen, J., (2009), The Effect of Motion Blur and Signal Noise on Image Quality in Low Light Imaging, Proceedings of SCIA,
    pp. 81-90.
  13. Ponomarenko, N., Battisti, F., Egiazarian, K., Carli, M., Astola, J., and Lukin, V.,(2009), Metrics Performance Comparison for Color Image Database, CD ROM Proceedings of VPQM, 6 p.
  14. Kendall, M.G., (1945), Advanced theory of statistics, London, UK, Charles Griffin&Company.
  15. Wang, Z., Simoncelli, E.P., and Bovik, A.C., (2003), Multi-scale structural similarity for image quality assessment, Proceedings of IEEE Asilomar Conference on Signals, Systems and Computers, 5p.
  16. Lukin, V., Zriakhov, M., Ponomarenko, N., Krivenko, S., and Miao, Z., (2010), Lossy Compression of Images without Visible Distortions and Its Application, Proceedings of International Conference on Signal Processing, 4 p.


pages 1343-1352

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