由於視訊編碼技術對於不同的視訊內文變化(VCV)會產生不同的編碼效能，針對不同的視訊內文變化來適應性的調整影像群(GOP)的大小有其必要。此外，當影像群內影像瞬間改變時也會影響著視訊編碼效能。因此，本論文提出一個結合適應性影像群偵測(AGD)與影像改變偵測(SCD)編碼演算法(JASC)來改善以H.264為基礎的增益視訊編碼(H.264/AVC)與可調性視訊編碼(H.264/SVC)。實驗結果證明本論文提出的方法節省了H.264/SVC的標準核心試驗(CE2)平均59%的運算時間並獲得89%的影像改變偵測率; 另外也改善了H.264/AVC平均0.62 dB的視訊品質，並獲得98%的影像改變偵測率。
由於目前最新的H.264/AVC與H.264/SVC是目前最新的視訊壓縮技術，但是其無失真影像壓縮編碼方法的壓縮性能卻遠低於過去的壓縮標準。另外，我們希望在一次編碼下，能夠同時實現失真、無失真與近似無失真影像壓縮位元串的概念，因而採用了H.264的失真影像編碼方法並視為第一層，第一層所產生的量化誤差將另外採用既有的內文式適應性二值化算數編碼(CABAC)來壓縮並視為差值層，實驗結果證明以H.264為基礎設計的二層式無失真影像編碼方法(two-layer H.264-LS)跟目前的無失真影像壓縮技術有較好的壓縮性能。
最後，我們提出兩個簡單的編碼方法來實現集合切割式階層樹(SPIHT)的快速演算法，實驗結果證明我們不但能夠降低編碼複雜度與時間30%，也同時降低大量的記憶體50%。

Video compression technology can result in different compression performance for different videos due to different VCV (video content variation) in the same target bitrate. It is important to adaptively adjust the GOP (group of pictures) for different VCV. Besides, the compression performance will be affected while a scene change occurs in a GOP. Therefore, in this paper, we suggest a joint AGD (adaptive GOP detection) and SCD (scene change detection) coding (JASC) algorithms to improve the H.264-based advance video coding (H.264/AVC) and scalable video coding (H.264/SVC). Simulation results show that H.264/SVC with JASC saves the computational time of 59% on average, and obtains the SCD detection rate of 89% than CE2 (core experiment 2); the H.264/AVC with JASC improves the PSNR of 0.62dB than the initial H.264/AVC, and obtains the SCD detection rate of 98%.
Although H.264/AVC and H.264/SVC are the newest video compression standards, the compression performance of H.264-based lossless (H.264-LS) image coding is dissatisfactory. In order to implement lossy, lossless and near lossless bestreams simultaneously, we suggest adopting the H.264-based lossy image coding which is regarded as first layer. The quantization error of the first layer is coded by existing CABAC which is regarded as different layer. Simulation results show that proposed two-layer H.264-based lossless (Two-layer H.264-LS) image coding has better compression performance than the past coders.
Finally, we suggest two simple methods to implement a fast set partitioning in hierarchical trees (SPIHT) algorithm. Simulation results show that proposed method decreases a lot of computational time and memory.

[1] T. Wiegand, G. J. Sullivan, G. Bjontegaard, and A. Luthra, “Overview of the H.264/AVC Video Coding Standard,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 13, no. 7, pp. 560–576, July 2003.
[2] ISO/IEC JTC1, Draft ITU-T Recommendation and Final Draft International Standard of Joint Video Specification (ITU-T Rec. H.264/ISO/IEC 14496-10 AVC, in Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG), JVTG050, March 2003.
[3] J. Reichel, H. Schwarz and M. Wien, Joint Scalable Video Model (JSVM) 1.0 Reference Encoding Algorithm Description, ISO/IEC JTC 1/SC 29/WG 11 N6899, Hong Kong, China, Jan. 2005.
[4] H. Schwarz, T. Hinz, H. Kirchhoffer, D. Marpe, and T. Wiegand, Technical Description of the HHI Proposal for SVC CE1, ISO/IEC JTC1/SC29/WG11, Document M11244, Palma de Mallorca, Spain, Oct. 2004.
[5] J. Reichel, H. Schwarz, and M. Wien, Joint Scalable Video Model 11 (JSVM 11), Joint Video Team, Doc. JVT-X202, Jul. 2007.
[6] H. Schwarz, D. Marpe and T. Wiegand, “Overview of the Scalable Video Coding Extension of the H.264/AVC Standard,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 17, no. 9, pp. 1103–1120, Sept. 2007.
[7] K. Mueller, P. Merkle, A. Smolic and T. Wiegand, Multiview Coding Using AVC, ISO/IEC JTC1/SC29/WG11, MPEG2006/m12945, Bangkok, Thailand, Jan. 2006.
[8] William B. Pennebaker and Joan L. Mitchell, JPEG: Still Image Data Compression Standard, Van Nostrand Reinhold, New York, 1992.
[9] D. S. Taubman and M. Marcellin, JPEG2000: Image Compression Fundamentals, Standards and Practice, Kluwer Academic Publishers, 2002.
[10] J. Valentim, P. Nunes, and F. Pereira, “Evaluating MPEG-4 Video Decoding Complexity for an Alternative Video Complexity Verifier Model,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 12, no. 11, pp. 1034–1044, Nov. 2002.
[11] G. H. Park, M. W. Park, S. Jeong, J. Cha, K. Kim, and J. Hong, Adaptive GOP Structure for SVC, MPEG Standards Contribution, m11563, Hong Kong, Jan. 2005.
[12] Y. Yokoyama, “Adaptive GOP Structure Selection for Real-time MPEG-2 Video Encoding,” IEEE International Conference on Image Processing, vol. 2, pp. 832–835, Sep. 2000.
[13] S. C. Hsia, S. C. Cheng, and C. L. Chen, “A Real-time Chip Implementation for Adaptive Video Coding Control,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 14, no. 8, pp. 1098–1104, Aug. 2004.
[14] A. Lan, A. Nguyen, and J. N. Hwang, “Scene Context Dependent Reference Frame Placement for MPEG Video Coding,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 9, no. 3, pp. 478–489, April 1999.
[15] J. Lee, I. Shin, and H. W. Park, "Adaptive Intra-Frame Assignment and Bit-Rate Estimation for Variable GOP Length in H.264," IEEE Trans. On Circuits and Systems for Video Technology, Vol. 16, no. 10, pp. 1271–1279, Oct. 2006.
[16] U. Gargi, R. Kasturi, and S. H. Strayer, “Performance Characterization of Video-shot-change Detection Methods,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 10, no. 1, pp. 1–13, Feb. 2000.
[17] R. Lienhart, “Comparison of Automatic Shot Boundary Detection Algorithms,” Storage and Retrieval for Still Image and Video Databases VII, Proc. SPIE, pp. 3656–29, Jan. 1999.
[18] C. W. Chiou, C. M. Tsai and C. W. Lin, “Fast Mode Decision Algorithms for Adaptive GOP Structure in the Scalable Extension of H.264/AVC,” IEEE International Symposium on Circuits and Systems, (ISCAS’07), pp. 3459–3462, May 2007.
[19] K. Wahid, V. Dimitrov, and G. Jullien, ”New Encoding of 8x8 DCT to make H.264 Lossless,” IEEE Asia Pacific Conference Circuits and Systems (APCCAS), pp. 780 – 783, Dec. 2006.
[20] S. Takamura and Y. Yashima, “H.264-based Lossless Video Coding Using Adaptive Transforms,” IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP ‘05). vol. 2, pp. 301–304, Mar. 2005.
[21] Y. L. Lee, K. H. Han, and G. J. Sullivan, “Improved Lossless Intra Coding for H.264/MPEG-4 AVC,” IEEE Trans. on Image Processing, vol. 15, no. 9, pp. 2610 – 2615, Sep. 2006.
[22] H. Schwarz, D. Marpe and T. Wiegand, “Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 13, no. 7, pp. 620 – 636, Jul. 2003.
[23] J. M. Shapiro, “Embedded Image Coding Using Zero-Trees of Wavelet Coefficients,” IEEE Trans. Signal Processing, vol. 41, no. 12, pp. 3445–3462. December 1993.
[24] A. Said and W. A. Pearlman, “A new, fast and efficient image codec based on set partitioning in hierarchical trees,” IEEE Trans. Circuits and Systems on Video Technology, vol. 6, no. 3, pp. 243–250, Jun. 1996.
[25] W. B. Pennebaker and J. L. Mitchell, “JPEG still image data compression standard,” Van Nostrand Reinhold, 1993.
[26] M. D. Adams, “The JPEG-2000 Still Image Compression Standard,” ISO/IEC JTC1/SC29/W0G1 (ITU-T SG8), 2001.
[27] D. Taubman, “High performance scalable image compression with EBCOT,” IEEE Trans. on Image Processing, vol. 9, no, 7, pp. 1158-1170, July 2000.
[28] W. B. Pennebaker, J. L. Mitchell, “Probability estimation for the Q-Coder,” IBM Journal of Research and Development, vol. 32, no. 6, pp. 737-752, Nov. 1988.
[29] Jian Zhu and S. Lawson, “Improvements to SPIHT for Lossy Image Coding,” IEEE International Conference on Electronics, Circuits and Systems, vol. 3, pp. 1363–1366, Sept. 2001.
[30] S. Jirachawang and V. Areekul, “Adaptive Directional Zero-Tree Image Coding,” Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS’03), vol. 2, pp.424 – 427, May 2003.
[31] Y. Sun, H. Zhang and G. Hu, “Real-Time Implementation of a New Low-Memory SPIHT Image Coding Algorithm Using DSP Chip,” IEEE Trans. on Image Processing, vol. 11, no. 9, pp. 1112–1116, Sept. 2002.
[32] W. A. Pearlman, A. Islam, N. Nagaraj, and A. Said, “Efficient, low complexity image coding with a set-partitioning embedded block coder,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 14, no. 11, pp. 1219–1235, Nov. 2004.
[33] S. T. Hsiang and John W. Woods, ”Embedded Video Coding Using Invertible Motion Compensated 3-D Subband/Wavelet Filter Bank,” Signal Processing: Image Commun., vol. 16, no. 8, pp. 705 – 724, May 2001.
[34] J. Andrew, “A Simple and Efficient Hierarchical Image Coder,” Proc. IEEE Int. Conf. Image Processing (ICIP), vol. 3, pp. 658–661, Oct. 1997.
[35] ITU-Telecommun. Standardization Sector, “H.26L Test Model Long Term Number 1 (TML-2) Draft 0,” Doc. Q15-I-57d0, Nov. 15, 1999.
[36] H. Li, Z. G. Li, and C. Wen, “Fast Mode Decision Algorithm for Inter-frame Coding in Fully Scalable Video Coding,” IEEE Trans. on Circuits and System for Video Technology, vol. 16, no. 7, pp. 889–896, July 2006.
[37] H. M. Wang, J. K. Lin and J. F. Yang, “Fast H.264 Inter Mode Decision Based on Inter and Intra Block Conditions,” IEEE International Symposium on Circuits and Systems, pp. 3647–3650, May 2007.
[38] C. H. Tseng, H. M. Wang, and J. F. Yang, “Enhanced Intra-4×4 Mode Decision for H.264/AVC Coders,” IEEE Trans. on Circuits and System for Video Technology, vol. 16, no. 8, pp. 1027–1032, Aug. 2006.
[39] S. Ma, W. Gao and Y. Lu, “Rate-Distortion Analysis for H.264/AVC Video Coding and its Application to Rate Control,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 15, no. 12, pp. 1533–1544, Dec. 2005.
[40] J. Y. Lee and H. W. Park, “A Rate Control Algorithm for DCT-based Video Coding using Simple Rate Estimation and Linear Source Model,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 15, no. 9, pp. 1077–1086, Sep. 2005.
[41] J. R. Ohm, “Three-dimensional Subband Coding with Motion Compensation,” IEEE Trans. on Image Processing, vol. 3, no. 5, pp. 559–571, Sep. 1994.
[42] S. J. Choi and John W. Woods, “Motion Compensated 3-D Subband Coding of Video,” IEEE Trans. on Image Processing, vol. 8, no. 2, pp. 155–167, Feb. 1999.
[43] M. Antonini, M. Barlaud, P. Mathieu and I. Daubechies, “Image Coding Using Wavelet Transform,” IEEE Trans. on Image Processing, vol. 1, no. 2, pp.205–220, Apr. 1992.
[44] ISO/IEC JTC1, Verification Model 18.0 of MPEG-4 Visual, ISO/IEC JTC1/WG11 Doc. N3908, Feb. 2001.
[45] L. Cao and C. W. Chen, “Content-based Multiple Bit stream Image Transmission over Noisy Channels,” IEEE Trans. on Image Processing, vol. 11, no. 11, pp. 1305–1313, Nov. 2002.
[46] R. L. Joshi et al., “Comparison of Different Methods of Classification in Subband Coding of Images,” IEEE Trans. on Image Processing, vol. 6, no. 11, pp. 1473–1485, Nov. 1997.
[47] Standard Test Images download: http://sipi.usc.edu/database/database.cgi?volume=misc, http://decsai.ugr.es/cvg/dbimagenes/c512.php.
[48] Draft Text of H.264/AVC Fidelity Range Extensions Amendment, Joint Video Team, DOC. JVT-L047, Redmond, USA, July 2004.
[49] http://www.hpl.hp.com/loco.
[50] M. Antonini, M. Barlaud, P. Mathieu and I. Daubechies, “Image Coding Using Wavelet Transform,” IEEE Trans. Image Process, vol. 1, no. 4, pp. 205–220, Apr. 1992.