research-article

Vector lifting schemes for stereo image coding

Authors:

Mounir Kaaniche,

Amel Benazza-Benyahia,

Béatrice Pesquet-Popescu,

Jean-Christophe PesquetAuthors Info & Claims

IEEE Transactions on Image Processing, Volume 18, Issue 11

Pages 2463 - 2475

https://doi.org/10.1109/TIP.2009.2026672

Published: 01 November 2009 Publication History

Abstract

Many research efforts have been devoted to the improvement of stereo image coding techniques for storage or transmission. In this paper, we are mainly interested in lossy-to-lossless coding schemes for stereo images allowing progressive reconstruction. The most commonly used approaches for stereo compression are based on disparity compensation techniques. The basic principle involved in this technique first consists of estimating the disparity map. Then, one image is considered as a reference and the other is predicted in order to generate a residual image. In this paper, we propose a novel approach, based on vector lifting schemes (VLS), which offers the advantage of generating two compact multiresolution representations of the left and the right views. We present two versions of this new scheme. A theoretical analysis of the performance of the considered VLS is also conducted. Experimental results indicate a significant improvement using the proposed structures compared with conventional methods.

References

[1]

D. Tzovaras, I. Kompatsiaris, and M. G. Strintzis, "3D object articulation and motion estimation in model-based stereoscopic videoconference image sequence analysis and coding," Image Commun. J., vol. 14, no. 10, pp. 817-840, Aug. 1999.

[2]

M. Z. Brown, D. Burschka, and G. D. Hager, "Advances in computational stereo," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 8, pp. 993-1008, Aug. 2003.

Digital Library

[3]

K. Tsutsui, S. Rokugawa, H. Nakagawa, S. Miyazaki, C.-T. Cheng, T. Shiraishi, and S.-D. Yang, "Detection and volume estimation of large-scale landslides based on elevation-change analysis using DEMs extracted from high-resolution satellite stereo imagery," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1681-1696, Jun. 2007.

[4]

G. W. Bothwell, E. G. Hansen, R. E. Vargo, and K. C. Miller, "The multi-angle imaging spectroradiometer science data system, its products, tools, and performance," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 7, pp. 1467-1476, Jul. 2002.

[5]

R. Lau, S. Ince, and J. Konrad, "Compression of still multiview images for 3-D automultiscopic spatially-multiplexed displays," in Proc. SPIE Conf. Stereoscopic Displays & Virtual Reality Systems, San Jose, CA, Jan. 28-Feb. 1 2007, vol. 6490, pp. 001-009.

[6]

M. E. Lukacs, "Predictive coding of multi-viewpoint image sets," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, Tokyo, Japan, Apr. 8-11, 1986, vol. 11, pp. 521-524.

[7]

M. G. Perkins, "Data compression of stereo pairs," IEEE Trans. Commun., vol. 40, no. 4, pp. 684-696, Apr. 1992.

[8]

N. Grammalidis and M. G. Strintzis, "Disparity and occlusion estimation in multiocular systems and their coding for the communication of multiview image sequences," IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 3, pp. 328-344, Jun. 1998.

Digital Library

[9]

W. Woo and A. Ortega, "Stereo image compression based on disparity field segmentation," in Proc. SPIE Conf. Visual Communications and Image Processing, San Jose, CA, Feb. 8-14, 1997, vol. 3024, pp. 391-402.

[10]

S. Wang and H. Chen, "An improved algorithm of motion compensation MPEG video compression," in Proc. Int. Vehicle Electronics Conf., Changchun, China, Sep. 6-9, 1999, vol. 1, pp. 261-264.

[11]

V. R. Dhond and J. K. Aggarwal, "Structure from stereo--A review," IEEE Trans. Syst., Man, Cybern., vol. 19, no. 6, pp. 1489-1510, Nov. 1989.

[12]

D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frames stereo correspondance algorithms," Int. J. Comput. Vis., vol. 47, no. 1, pp. 7-42, June. 2002.

Digital Library

[13]

W. Woo and A. Ortega, "Overlapped block disparity compensation with adaptive windows for stereo image coding," IEEE Trans. Circuits Syst. Video Technol., vol. 10, no. 2, pp. 194-200, March 2000.

Digital Library

[14]

S. Sodagari and E. Dubois, "Variable-block size disparity estimation in stereoscopic imagery," in Proc. IEEE Canadian Conf. Electrical and Computer Engineering, Montreal, Canada, May 4-7, 2003, vol. 3, pp. 2047-2049.

[15]

H. Aydinoglu and M. Hayes, "Stereo image coding," in Proc. Int. Symp. Circuits and Systems, Washington, DC, Apr. 30-May 3, 1995, vol. I, pp. 247-250.

[16]

N. V. Boulgouris and M. G. Strintzis, "A family of wavelet-based stereo image coders," IEEE Trans. Circuits Syst. Video Technol., vol. 12, no. 10, pp. 898-903, Oct. 2002.

Digital Library

[17]

J. M. Shapiro, "Embedded image coding using zerotrees of wavelet coefficients," IEEE Trans. Signal Process., vol. 41, no. 12, pp. 3445-3462, Dec. 1993.

Digital Library

[18]

Q. Jiang, J. J. Lee, and M. H. Hayes, "A wavelet based stereo image coding algorithm," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, Phoenix, AZ, Mar. 14-18, 1999, vol. 6, pp. 3157-3160.

Digital Library

[19]

D. Taubman and M. Marcellin, JPEG2000: Image Compression Fundamentals, Standards and Practice. Norwell, MA: Kluwer, 2004.

Digital Library

[20]

A. Benazza-Benyahia, J.-C. Pesquet, and M. Hamdi, "Vector lifting schemes for lossless coding and progressive archival of multispectral images," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 9, pp. 2011-2024, Sep. 2002.

[21]

M. Kaaniche, A. Benazza-Benyahia, J.-C. Pesquet, and B. Pesquet-Popescu, "Lifting schemes for joint coding of stereoscopic pairs of satellite images," in Proc. European Signal and Image Processing Conf., Poznán, Poland, Sep. 3-7, 2007, pp. 981-984.

[22]

S. G. Mallat, A Wavelet Tour of Signal Processing. San Diego, CA: Academic, 1998.

Digital Library

[23]

W. Sweldens, "The lifting scheme: A new philosophy in biorthogonal wavelet constructions," in Wavelet Applications in Signal and Image Processing III, SPIE, San Diego, CA, Sep. 1995, vol. 2569, pp. 68-79.

[24]

F. J. Hampson and J.-C. Pesquet, "A nonlinear subband decomposition with perfect reconstruction," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Atlanta, GA, May 7-10, 1996, vol. 3, pp. 1523-1526.

Digital Library

[25]

A. Gouze, M. Antonini, M. Barlaud, and B. Macq, "Design of signal-adapted multidimensional lifting schemes for lossy coding," IEEE Trans. Image Process., vol. 13, no. 12, pp. 1589-1603, Dec. 2004.

Digital Library

[26]

B. Pesquet-Popescu, "Two-Stage Adaptive Filter Bank," European patent number EP1119911, first filling date 1999/07/27, official filling number 99401919.8.

[27]

B. Belzer, J.-M. Lina, and J. Villasenor, "Complex, linear-phase filters for efficient image coding," IEEE Trans. Acoust., Speech, Signal Process., vol. 43, no. 10, pp. 2425-2427, Oct. 1995.

Digital Library

[28]

A. Gersho and R. M. Gray, Vector Quantization and Signal Compression . Norwell, MA: Kluwer, 1993.

Digital Library

[29]

N. S. Jayant and P. Noll, Digital Coding of Waveforms. Englewood Cliffs, NJ: Prentice-Hall, 1984.

[30]

A. Said and W. A. Pearlman, "A new fast and efficient image codec based on set partitionning in hierarchical trees," IEEE Trans. Circuits Syst. Video Technol., vol. 6, pp. 243-250, Jun. 1996.

Digital Library

[31]

D. Taubman, "High performance scalable image compression with EBCOT," IEEE Trans. Image Process., vol. 9, no. 7, pp. 1158-1170, Jul. 2000.

Digital Library

[32]

S.-T. Hsiang and J. W. Woods, "Embedded image coding using zeroblocks of subband/wavelet coefficients and context modeling," in Proc. IEEE Int. Symp. Circuits and Systems, Geneva, Switzerland, May 28-31, 2000, vol. 3, pp. 662-665.

[33]

Z. Arnavut and S. Narumalani, "Application of permutations to lossless compression of multispectral thematic mapper images," Opt. Eng., vol. 35, no. 12, pp. 3442-3448, 1996.

[34]

A. Benazza-Benyahia and J.-C. Pesquet, "Vector-lifting schemes based on sorting techniques for lossless compression of multispectral images," in Proc. SPIE Conf. Mathematics of Data/Image Coding, Compression and Encryption IV, With Applications, Seattle,WA, Jul. 7-11, 2002, vol. 4793, pp. 42-51.

[35]

B. Pesquet-Popescu and V. Bottreau, "Three-dimensional lifting schemes for motion compensated video compression," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Salt Lake City, UT, May 7-11, 2001, vol. 3, pp. 1793-1796.

Digital Library

[36]

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Trans. Image Process., vol. 13, no. 4, pp. 600-612, Apr. 2004.

Digital Library

Cited By

Dardouri TKaaniche MBenazza-Benyahia ADauphin GPesquet J(2024)Joint Learning of Fully Connected Network Models in Lifting Based Image CodersIEEE Transactions on Image Processing10.1109/TIP.2023.333327933(134-148)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIP.2023.3333279
Dardouri TKaaniche MBenazza-Benyahia APesquet J(2022)Dynamic Neural Network for Lossy-to-Lossless Image CodingIEEE Transactions on Image Processing10.1109/TIP.2021.313282531(569-584)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TIP.2021.3132825
Hachicha WKaaniche MBeghdadi ACheikh F(2017)No-reference stereo image quality assessment based on joint wavelet decomposition and statistical modelsImage Communication10.1016/j.image.2017.03.00554:C(107-117)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.image.2017.03.005
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Published In

cover image IEEE Transactions on Image Processing

IEEE Transactions on Image Processing Volume 18, Issue 11

November 2009

223 pages

ISSN:1057-7149

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Copyright © 2009.

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IEEE Press

Publication History

Published: 01 November 2009

Revised: 21 May 2009

Received: 24 July 2008

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Cited By

Dardouri TKaaniche MBenazza-Benyahia ADauphin GPesquet J(2024)Joint Learning of Fully Connected Network Models in Lifting Based Image CodersIEEE Transactions on Image Processing10.1109/TIP.2023.333327933(134-148)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIP.2023.3333279
Dardouri TKaaniche MBenazza-Benyahia APesquet J(2022)Dynamic Neural Network for Lossy-to-Lossless Image CodingIEEE Transactions on Image Processing10.1109/TIP.2021.313282531(569-584)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TIP.2021.3132825
Hachicha WKaaniche MBeghdadi ACheikh F(2017)No-reference stereo image quality assessment based on joint wavelet decomposition and statistical modelsImage Communication10.1016/j.image.2017.03.00554:C(107-117)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.image.2017.03.005
Hachicha WKaaniche MBeghdadi ACheikh F(2015)Efficient Inter-View Bit Allocation Methods for Stereo Image CodingIEEE Transactions on Multimedia10.1109/TMM.2015.241709917:6(765-777)Online publication date: 1-Jun-2015
https://dl.acm.org/doi/10.1109/TMM.2015.2417099
Chaker AKaaniche MBenazza-Benyahia A(2015)Disparity based stereo image retrieval through univariate and bivariate modelsImage Communication10.1016/j.image.2014.12.00431:C(174-184)Online publication date: 1-Feb-2015
https://dl.acm.org/doi/10.1016/j.image.2014.12.004
Kaaniche MMiled WPesquet-Popescu BBenazza-Benyahia APesquet J(2009)Dense disparity MAP representations for stereo image codingProceedings of the 16th IEEE international conference on Image processing10.5555/1818719.1818935(725-728)Online publication date: 7-Nov-2009
https://dl.acm.org/doi/10.5555/1818719.1818935

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