3維(3D)小波轉換(wavelet)已經應用在視訊編解碼器，以產生品質可調性的碼流，以利在異質性的網路上傳輸。然而在此架構下的重建視訊由於失真的不平均分配，導致有著時間上品質波動的現象。以模型推論來達到平滑時間上視訊品質的小波編碼器已經被提出來，而本篇論文提出以真實訊號失真傳遞特性為基礎的位元率分配演算法來達到時間品質上的一致。影質控制從一個影像堆(GOP)內，至GOP之間以達到全域影質的穩定。另外我們利用誤差對位元率的特性，提出可以大幅降低記憶體空間以及時間延遲的影質控制法。此演算法擁又下列特性：(1)低時間複雜度;(2)大幅降低重建影像PSNR的波動;(3) 增加在及時(real-time)系統的可行性。實驗結果顯示此演算法可以產生比3D-SPIHT與MC-EZBC 低的影質波動碼流。

Three-dimensional (3D) wavelet transforms have been used in video codecs (WVC) to generate quality scalable bitstreams for communications over heterogeneous networks. However, reconstructed pictures of 3D-WVC suffer temporal quality fluctuations due to unequal distortion distributions in the code/decode process. Theoretical WVC coding models had been proposed to smooth temporal picture quality fluctuations. However, in practical coding processes, signal properties do not comply with assumptions in the ideal WVC model. We propose to bridge this gap between ideal and practical signal properties to improve the temporal quality smoothness (TS) of WVC. The relation between distortions of subbands and qualities of reconstructed pictures of one WVC was exploited, from which the TS algorithm was developed. The most important features of the proposed TS-WVC method are: 1) low computation complexity; 2) largely reduce the temporal picture quality variations; and 3) make it feasible for real-time WVC applications.

[1] B.-J. Kim, Z. Xiong and W. A. Pearlman, “Low bit-rate scalable video coding with
3-D set partitioning in hierarchical trees (3-D SPIHT),” IEEE Trans. on Circuits
and Systems for Video Technology, vol. 10, no. 8, Dec. 2000.
[2] G. Karlsson,and M. Vetterli, “Three dimensional sub-band coding of video,” International
Conf. on Acoustics, Speech, and Signal Processing, vol. 2, pp. 1100-1103,
April 1998.
[3] D. Taubman and A. Zakhor, “Multirate 3-D subband coding of video,” IEEE Trans.
on Image Processing, vol. 3, no. 5, Sep. 1994.
[4] S. Somasundaram and K.P. Subbalakshmi, “A novel 3D scalable video compression
algorithm,” SPIE Image and Video Communications and Processing, vol. 5022, pp.
966-972, 2003.
[5] V. Bottreau, M. Benetiere, and B. Felts, “A fully scalable 3D subband video codec,”
IEEE ICIP, vol. 2, pp. 1017-1020, Oct. 2001.
[6] J. Xu, Z. Xiong, S. Li and Y.-Q. Zhang, “Memory-constrained 3-D wavelet transform
for video coding without boundary effects,” IEEE Trans. on Circuits and Systems
for Video Technology, vol. 12, no. 9, Sep. 2002.
[7] S. J. Choi and J. Woods, “Motion-compensated 3-D subband coding of video,” IEEE
Trans. on Image Processing, vol. 8, no. 2, pages 155-167, Feb 1999.
[8] J.R. Ohm, “Three-dimensional subband coding with motion compenstation,” IEEE
Trans. Image Processing, vol. 3, no. 5, pp. 559-571, 1994.
[9] D. S. Taubman, et al, “JPEG2000: Image Compression Fundamentals, Standards,
and Practice,” Kluwer International Series in Engineering and Computer Science,
642.
[10] P.-Y. Cheng, “Rate-distortion optimized bit rate control scheme for a wavelet video
coder,” IEEE Trans. on Circuits and Systems for Video Technology, vol.7, no. 4, pp.
696-702, 1997.
[11] J. C. Dagher, et al, “Resource-constrained rate control for motion JPEG2000,”
IEEE Trans. on Image Processing, vol. 12, no. 12, Dec. 2003.
[12] L. Luo, et al, “Rate control with smoothed temporal distortion for a 3D embedded
wavelet video coder,” IEEE Conf. Information, Communications & Signal Processing,
Oct. 2001.
[13] N. Mehrseresht and D. Taubman, “Adaptively weighted update steps in motion
compensated lifting based scalable video compression,” IEEE ICIP 2003,
Barcelona, Spain ,Sept. 2003.
[14] A. Mavlankar and E. Steinbach, “Distortion prediction for motion-compensated
lifted haar wavelet transform and its application to rate allocation,” Proc. IEEE
International Picture Coding Symposium (PCS), San Francisco, U.S.A., Dec. 2004.
[15] A. Mavlankar, et al, “A New Update Step for Reduction of PSNR Fluctuations in
Motion-Compenated LiftedWavelet Video Coding,” Proc. IEEE InternationalWorkshop
on Multimedia Signal Processing (MMSP), Shanghai, China, Nov. 2005.
[16] P. Chen, K. Hanke, T. Rusert and J. W. Woods, “Improvements to the MC-EZBC
scalable video coder,” Proc. ICIP 2003 ,vol. 2, p:II - 81-4, Sept. 2003.
[17] J.-J. Chen and K.-W. Wang, “A temporal quality smooth method for wavelet video
coders,” IEEE International Conf. on Multimedia & Expo, 2005.
[18] L. Overmeire, et al, “Constant quality video coding using video content analysis,”
Signal Processing: ImageCommunication, vol. 20, issue 4, Apr. 2005.
[19] J.Pan and B.Hu, “Adaptive GOF residual operation algorithm in video compression,”
Proc. SPIE Visual Communication and Image Processing, vol.5960, pp.661-
670, Jul. 2005.
[20] E. Balster and Y.-F. Zheng, “Constant quality rate control for content-based 3D
wavelet video communication,” Proc. IEEE Intelligent Control and Automation,
vol.3, pp.2056-2060, Jul. 2005.
[21] D. Turaga and M. van der Schaar, “Wavelet coding for video streaming using
new unconstrained motion compensated temporal filtering, Proc. Infernational
Workhop on Digital Communicntions: Advanced Methods for Multimedia Signal
Processing, lWDC2002, Capri, Italy, pp. 4148, Sept. 2002.
[22] A. Munteanu, et al , “Control of the distortion variation in video coding systems
based on motion compensated temporal filtering,” IEEE Conf. Image Processing,
Sept. 2003.
[23] Official website of h.26x and MPEG4: http://www.h263l.com
[24] Weiping Li, “Overview of fine granularity scalability in MPEG-4 video standard,”
IEEE Trans. CSVT. vol. 11, no. 3, pp. 301-317, 2001.
[25] J.R. Ohm, “Advances in Scalable Video Coding,” Proc. of IEEE, vol. 93, no. 1, Jan.
2005.
[26] C. Sidney Burrus, Ramesh A. Copmath, and Haitao Guo, “Introduction to
wavelets and Wavelet Transform,” Pretice-Hall, 1998.
[27] D. S. Taubman and M. W. Marcellin, “JPEG2000: image compression fundamentals,
standards and practice,” Kluwer Academic Publishers, 2002.
[28] S.-T. Hsiang, “Embedded image coding using zeroBlocks of Subband/Wavelet coefficients
and context modeling,” IEEE Data Compression Conference, pp. 83-92,
Snow Bird, UT, Mar. 2001.
[29] A. Said and W. A. Pearlman, “A new fast and efficient image codec based on set
partitioning in hierarchical trees,” IEEE Trans. Circuits Syst. Video Technol., vol.
6, pp. 243V250, June 1996.
[30] M. Antononi, et al, “Image coding using wavelet transform,” IEEE Trans. on Image
Processing, vol. 1, pp. 205-220, 1992.
[31] J.-J. Chen and David W Lin, “Optimal bit allocation for Coding of Video signals
over ATM networks, ”IEEE Journal on Selected Areas in Communications, vol. 15,
No. 6, Aug. 1997.