A New Object-Based Fractal Compression of Monocular and Stereo Video Sequences
Abstract
A novel object-based fractal monocular and stereo video compression scheme with quadtree-based motion and disparity compensation is proposed in this paper. Fractal coding is adopted and each object is encoded independently by a prior image segmentation alpha plane, which is defined exactly as in MPEG-4. The first n frames of right video sequence are encoded by using the Circular Prediction Mapping (CPM) and the remaining frames are encoded by using the Non Contractive Interframe Mapping (NCIM). The CPM and NCIM methods accomplish the motion estimation/compensation of right video sequence. According to the different coding or user requirements, the spatial correlations between the left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/compensation, or simply by applying CPM/NCIM on left video sequence. The testing results with monocular and stereo video sequences provide promising performances at low bit rate coding. We believe it will be a powerful and efficient technique for the object-based monocular and stereo video sequences coding.
Keywords
Monocular and stereo video coding fractal coding object-based coding low bit rate codingPreview
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References
- 1.Konrad, J.: Visual communication of tomorrow: natural, efficient, and flexible. IEEE Commun. Mag. 39(1), 126–133 (2001)CrossRefGoogle Scholar
- 2.Wang, Y., Ostermann, J., Zhang, Y.Q.: Video processing and communications, p. 595. Prentice-Hall, Englewood Cliffs (2002)Google Scholar
- 3.Roy Chowdhury, A.: Statistical analysis of 3D modeling from monocular video streams, PhD Thesis, Univ. of Maryland (2002)Google Scholar
- 4.Lim, J., Ngan, K.N., Yang, W., Sohn, K.: A multiview sequence CODEC with view scalability. Signal Processing: Image Communications 19(3), 239–256 (2004)Google Scholar
- 5.Tzovaras, D., Grammalidis, N., Strintzis, M.G.: Disparity field and depth map coding for multiview 3D image generation. Signal Processing: Image Comm. 11(3), 205–230 (1998)Google Scholar
- 6.Tzovaras, D., Grammalidis, N., Strintzis, M.G., Malassiotis, S.: Coding for the storage and communication of visualisations of 3D medical data. Signal Processing: Image Communication 13(1), 65–87 (1998)Google Scholar
- 7.Boulgouris, N.V., Strintzis, M.G.: A family of wavelet-based stereo image coders. IEEE Trans. Circuits Syst. Video Technol. 12(10), 898–903 (2002)CrossRefGoogle Scholar
- 8.Strintzis, M.G., Malassiotis, S.: Object-based coding of stereoscopic and 3D image sequences. IEEE Signal Proc. Mag. 16(3), 14–28 (1999)CrossRefGoogle Scholar
- 9.Sikora, T., Makai, B.: Shape-adaptive DCT for generic coding of video. IEEE Trans. Circuits Syst. Video Technol. 5, 59–62 (1995)CrossRefGoogle Scholar
- 10.Special issue on object-based video coding, IEEE Trans. Circuit Syst. Video Technol., vol. 9 (December 1999)Google Scholar
- 11.Salembier, P., et al.: Segmentation-based video coding system allowing the manipulation of objects. IEEE Trans. Circuits Syst. Video Technol. 7, 60–74 (1997)CrossRefGoogle Scholar
- 12.Castagno, R., Ebrahimi, T., Kunt, M.: Video segmentation based on multiple features for interactive multimedia applications. IEEE Trans. Circuits Syst. Video Technol. 8(5), 562–571 (1998)CrossRefGoogle Scholar
- 13.Ida, T., Sambonsugi, Y.: Image segmentation and contour detection using fractal coding. IEEE Trans. Circuits Syst. Video Technol. 8(8), 968–975 (1998)CrossRefGoogle Scholar
- 14.Ida, T., Sambonsugi, Y.: Self-affine mapping system and its application to object contour extraction. IEEE Trans. Image Processing 9(11), 1926–1936 (2000)MathSciNetCrossRefMATHGoogle Scholar
- 15.Fisher, Y., Shen, T.P., Rogovin, D.: Fractal (Self-VQ) encoding of video sequences. In: VCIP, vol. 2308, pp. 1359–1370 (1994)Google Scholar
- 16.Kim, C.S., Kim, R.C., Lee, S.U.: Fractal coding of video sequence using circular prediction mapping and noncontractive interframe mapping. IEEE Trans. Image Proc. 7(4), 601–605 (1998)CrossRefGoogle Scholar
- 17.Franich, R.E.H., Lagendijk, R.L., Biemond, J.: Fractal coding in object-based system. In: Proc. IEEE Int. Conf. Image Processing, Austin, Texas, USA, pp. 405–408 (1994)Google Scholar
- 18.Fisher, Y.: Fractal encoding with quadtrees. In: Fisher, Y. (ed.) Fractal Image Compression: Theory and Applications to Digital Images, pp. 55–77. Springer, New York (1995)CrossRefGoogle Scholar
- 19.Belloulata, K., Stasinski, R., Konrad, J.: Region-based image compression using fractals and shape-adaptive DCT. In: Proc. IEEE Int. Conf. Image Processing, October 1999, vol. II, pp. 815–819 (1999)Google Scholar
- 20.Belloulata, K., Konrad, J.: Fractal image compression with region-based functionality. IEEE Trans. Image Processing 11(4), 351–362 (2002)CrossRefGoogle Scholar
- 21.Hartenstein, H., Ruhl, M., Saupe, D.: Region-based fractal image compression. IEEE Trans. Image Processing 9(7), 1171–1184 (2000)CrossRefGoogle Scholar
- 22.Zhu, S., Belloulata, K.: Region-Based Fractal Coding of Monocular and Stereo Video Sequences. In: Proc. the 6th IASTED International Conference on Signal and Image Processing, Honolulu, Hawaii, USA, August 23-25, 2004, pp. 308–313 (2004)Google Scholar
- 23.Zhu, S., Belloulata, K.: Object-based fractal coding of video sequence. In: IEEE International Workshop on Non Linear Signal and Image Processing, Sapporo, Japan, May 22-23 (2005)Google Scholar
- 24.Belloulata, K., Zhu, S.: A new object-based fractal stereo codec with quadtree-based disparity or motion compensation. In: Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Toulouse, France, May 2006, vol. II, pp. 481–484 (2006)Google Scholar
- 25.Domaszewicz, J., Vaishampayan, V.A.: Graph-theoretical analysis of the fractal transform. In: Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, April 1995, vol. IV, pp. 2559–2562 (1995)Google Scholar
- 26.Special issue on 3-D video technology. IEEE Trans. Circuits Syst. Video Technol. 10(2-4) (June 2000)Google Scholar
- 27.Wang, R.S., Wang, Y.: Multiview video sequence analysis, compression, and virtual viewpoint synthesis. IEEE Trans. Circuit Syst. Video Technol. 10(3), 397–410 (2000)CrossRefGoogle Scholar
- 28.Naemura, T., Harashima, H.: Fractal coding of a multi-view 3-D image. In: Proc. IEEE Int. Conf. Image Processing, Texas, USA, November 1994, vol. III, pp. 129–132 (1994)Google Scholar
- 29.Yang, W., Ngi, N.K.: MPEG-4 based stereoscopic video sequences encoder. In: Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Montréal, Canada, May 2004, pp. 741–744 (2004)Google Scholar