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Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform

EURASIP Journal on Image and Video Processing volume 2007, Article number: 078323 (2007) Cite this article

Abstract

Object-based image coding is drawing a great attention for the many opportunities it offers to high-level applications. In terms of rate-distortion performance, however, its value is still uncertain, because the gains provided by an accurate image segmentation are balanced by the inefficiency of coding objects of arbitrary shape, with losses that depend on both the coding scheme and the object geometry. This work aims at measuring rate-distortion costs and gains for a wavelet-based shape-adaptive encoder similar to the shape-adaptive texture coder adopted in MPEG-4. The analysis of the rate-distortion curves obtained in several experiments provides insight about what performance gains and losses can be expected in various operative conditions and shows the potential of such an approach for image coding.

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References

  1. Kunt M, Benard M, Leonardi R: Recent results in high-compression image coding. IEEE Transactions on Circuits and Systems 1987,34(11):1306-1336. 10.1109/TCS.1987.1086071

    Article  Google Scholar 

  2. ISO/IEC JTC1 ISO/IEC 14496-2: coding of audio-visual objects April 2001

  3. Madhavi M, Fowler JE: Unequal error protection of embedded multimedia objects for packet-erasure channels. Proceedings of the IEEE International Workshop on Multimedia Signal Processing, December 2002, St. Thomas, Virgin Islands, USA 61-64.

    Google Scholar 

  4. Gan T, Ma K-K: Weighted unequal error protection for transmitting scalable object-oriented images over packet-erasure networks. IEEE Transactions on Image Processing 2005,14(2):189-199. 10.1109/TIP.2004.840692

    Article  MathSciNet  Google Scholar 

  5. Fowler JE, Fox DN: Wavelet-based coding of three-dimensional oceanographic images around land masses. Proceedings of IEEE International Conference on Image Processing (ICIP '00), September 2000, Vancouver, BC, Canada 2: 431-434.

    Google Scholar 

  6. Taubman D: High performance scalable image compression with EBCOT. IEEE Transactions on Image Processing 2000,9(7):1158-1170. 10.1109/83.847830

    Article  Google Scholar 

  7. Skodras A, Christopoulos C, Ebrahimi T: The JPEG2000 still image compression standard. IEEE Signal Processing Magazine 2001,18(5):36-58. 10.1109/79.952804

    Article  Google Scholar 

  8. Xie G, Shen H: Highly scalable, low-complexity image coding using zeroblocks of wavelet coefficients. IEEE Transactions on Circuits and Systems for Video Technology 2005,15(6):762-770. 10.1109/TCSVT.2005.848311

    Article  Google Scholar 

  9. Sun X, Foote J, Kimber D, Manjunath BS: Region of interest extraction and virtual camera control based on panoramic video capturing. IEEE Transactions on Multimedia 2005,7(5):981-990. 10.1109/TMM.2005.854388

    Article  Google Scholar 

  10. Li S, Li W: Shape-adaptive discrete wavelet transforms for arbitrarily shaped visual object coding. IEEE Transactions on Circuits and Systems for Video Technology 2000,10(5):725-743. 10.1109/76.856450

    Article  Google Scholar 

  11. Cagnazzo M, Poggi G, Verdoliva L, Zinicola A: Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT. Proceedings of IEEE International Conference on Image Processing (ICIP '04), October 2004, Singapore 4: 2459-2462.

    Google Scholar 

  12. Kawanaka A, Algazi VR: Zerotree coding of wavelet coefficients for image data on arbitrarily shaped support. Proceedings of the Data Compression Conference (DCC '99), March 1999, Snowbird, Utah, USA 534.

    Google Scholar 

  13. Minami G, Xiong Z, Wang A, Mehrotra S: 3-D wavelet coding of video with arbitrary regions of support. IEEE Transactions on Circuits and Systems for Video Technology 2001,11(9):1063-1068. 10.1109/76.946523

    Article  Google Scholar 

  14. Said A, Pearlman WA: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits and Systems for Video Technology 1996,6(3):243-250. 10.1109/76.499834

    Article  Google Scholar 

  15. Egger O, Fleury P, Ebrahimi T, Kunt M: High-performance compression of visual information-a tutorial review—I: still pictures. Proceedings of the IEEE 1999,87(6):976-1011. 10.1109/5.763312

    Article  Google Scholar 

  16. 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

    Article  Google Scholar 

  17. Sikora T: Trends and perspectives in image and video coding. Proceedings of the IEEE 2005,93(1):6-17. 10.1109/JPROC.2004.839601

    Article  MathSciNet  Google Scholar 

  18. Tian J, Wells R Jr.: Embedded image coding using wavelet difference reduction. In Wavelet Image and Video Compression. Edited by: Topiwala P. Kluwer Academic, Norwell, Mass, USA; 1998:289-301.

    Google Scholar 

  19. Lu Z, Pearlman WA: Wavelet coding of video object by object-based SPECK algorithm. Proceedings of the 22nd Picture Coding Symposium (PCS '01), April 2001, Seoul, Korea 413-416.

    Google Scholar 

  20. Liu Z, Hua J, Xiong Z, Wu Q, Castleman K: Lossy-to-lossless ROI coding of chromosome images using modified SPIHT and EBCOT. Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI '02), July 2002, Washington, DC, USA 317-320.

    Google Scholar 

  21. Fowler JE: Shape-adaptive tarp coding. Proceedings of IEEE International Conference on Image Processing (ICIP '03), September 2003, Barcelona, Spain 1: 621-624.

    Google Scholar 

  22. Fowler JE: Shape-adaptive coding using binary set splitting with K-D trees. Proceedings of IEEE International Conference on Image Processing (ICIP '04), October 2004, Singapore 5: 1301-1304.

    MathSciNet  Google Scholar 

  23. Prandoni P, Vetterli M: Approximation and compression of piecewise smooth functions. Philosophical Transactions: Mathematical, Physical and Engineering Sciences 1999,357(1760):2573-2591. 10.1098/rsta.1999.0449

    Article  MathSciNet  MATH  Google Scholar 

  24. Ratnakar V: RAPP: lossless image compression with runs of adaptive pixel patterns. Proceedings of the 32nd Asilomar Conference on Signals, Systems & Computers, November 1998, Pacific Grove, Calif, USA 2: 1251-1255.

    Google Scholar 

  25. Goyal VK: Theoretical foundations of transform coding. IEEE Signal Processing Magazine 2001,18(5):9-21. 10.1109/79.952802

    Article  Google Scholar 

  26. Katto J, Yasuda Y: Performance evaluation of subband coding and optimization of its filter coefficients. Visual Communications and Image Processing, November 1991, Boston, Mass, USA, Proceedings of SPIE 1605: 95-106.

    Google Scholar 

  27. Usevitch BE: Optimal bit allocation for biorthogonal wavelet coding. Proceedings of the 6th Data Compression Conference (DCC '96), March-April 1996, Snowbird, Utah, USA 387-395.

    Chapter  Google Scholar 

  28. Cagnazzo M, Poggi G, Verdoliva L: Costs and advantages of shape-adaptive wavelet transform for region-based image coding. Proceedings of IEEE International Conference on Image Processing (ICIP '05), September 2005, Genova, Italy 3: 197-200.

    Google Scholar 

  29. http://sipi.usc.edu/database/

  30. Cagnazzo M, Gaetano R, Poggi G, Verdoliva L: Region based compression of multispectral images by classified KLT. Proceedings of IEEE International Conference on Image Processing (ICIP '06), October 2006, Atlanta, Ga, USA

    Google Scholar 

  31. Fowler JE: QccPack: an open-source software library for quantization, compression, and coding. Applications of Digital Image Processing XXIII, July 2000, San Diego, Calif, USA, Proceedings of SPIE 4115: 294-301.

    Article  Google Scholar 

  32. http://qccpack.sourceforge.net/

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Authors and Affiliations

  1. Dipartimento di Ingegneria Elettronica e delle Telecomunicazioni, Università Federico II di Napoli, Via Claudio 21, Napoli, 80125, Italy

    Marco Cagnazzo, Sara Parrilli, Giovanni Poggi & Luisa Verdoliva

Authors
  1. Marco Cagnazzo
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  2. Sara Parrilli
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  3. Giovanni Poggi
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  4. Luisa Verdoliva
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Corresponding author

Correspondence to Marco Cagnazzo.

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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.

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Cagnazzo, M., Parrilli, S., Poggi, G. et al. Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform. J Image Video Proc 2007, 078323 (2007). https://doi.org/10.1155/2007/78323

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  • DOI: https://doi.org/10.1155/2007/78323

Keywords

  • Image Processing
  • Pattern Recognition
  • Computer Vision
  • Image Segmentation
  • Wavelet Transform