基于H.264的视频编码快速算法及复杂度—失真模型研究
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摘要
随着经济发展和技术进步,市场对高性能视频业务的需求不断膨胀,原有视频编码标准已不能满足要求。2003年,ITU-T的视频编码专家组VCEG及ISO/IEC的运动图像专家组MPEG联合制定了新一代视频编码标准H.264/AVC,该标准具有很高的压缩效率和良好的网络适应能力,将在数字视频通信和存储领域得到广泛应用。
然而,H.264的高压缩效率是以高计算复杂度为代价的,其高度的计算复杂性已造成软硬件实现的瓶颈,因此建立低复杂度的视频编码器就显得尤为重要;另外在软件编解码情况下,可利用的处理器资源随不同平台或占用该资源的任务数量而变化,要求计算复杂度不再固定。在以电池为驱动的手持终端上,考虑到功耗问题,也要求编码复杂度随时可控。目前,面向H.264开展快速编码算法研究以及复杂度-失真研究已成为业界和学术界关注的热点。本文针对这两方面开展了以下创新性研究:
首先,对于H.264参考编码器JM中比较耗时的帧间模式选择和运动估计模块,本文分别提出了自适应的帧间模式选择算法和多参考帧快速选择算法,并在此基础上对JM进行了局部代码优化,建立了低复杂度的视频编码器JM_OPT。
其次,综合分析运动估计模块各编码参数对复杂度、失真和编码比特率的影响,针对JM_OPT提出了复杂度可分级的运动估计算法;考虑H.264整数变换、量化和Zig-zag扫描的特点,基于DCT截断思想提出了复杂度可分级的DCT算法。通过对这两种算法进行综合考虑,针对JM_OPT建立了基于参数的复杂度可分级的视频编码框架,通过调节复杂度控制参数即可实现复杂度的可分级性,从而在视频质量和复杂度间形成良好折中。
在此基础上,针对复杂度控制和码率控制的特点,本文提出了帧间复杂度最优分配算法以及复杂度-速率联合控制策略,建立了复杂度-失真模型,该模型能根据终端处理器的计算能力或者功耗的变化自适应进行计算复杂度的调整。考虑智能手机在计算能力、内存和功耗等方面的特点,本文最后在智能手机模拟器上对复杂度-失真模型进行了仿真,实验结果验证了该模型的可行性。
With the economic development and technological progress, the market has increasing demands of high-performance video service. In this case, the previous video coding standards can’t meet the requirement. In 2003, the ITU-T VCEG and the ISO/IEC MPEG jointly developed a new generation video coding standard H.264/AVC, which has higher compression efficiency and improved network adaptation. Hence it will have a broad application in digital video communication and storage areas in the future.
However, the high compression efficiency of H.264 is at the cost of high computational complexity, which has become the bottleneck in the realization of software and hardware, therefore it is very important to develop a low complexity video encoder. Furthermore, in the condition of software coding and decoding, the available processor resource will change with the different platforms or assignment quantities occupying the processor resource, which requests that the encoder has unfixed computational complexity. The handset drived by the battery also requires that the coding complexity can be controlled considering the limited power consumption. Currently,the research on fast coding algorithms and complexity- distortion for H.264 have been one of the hotspot issues in both industry and academia. The following creative studies are performed according to the two aspects:
Firstly, for the time-consuming modules of inter-frame mode selection and motion estimation in H.264 reference encoder JM, an adaptive inter-frame mode decision algorithm and a multi-reference frames fast selection algorithm are proposed respectively in this paper. On the basis, local codes of JM are optimized and a low complexity video encoder JM_OPT is developed.
Secondly, a complexity scalable motion estimation arithmetic aimed at JM_OPT is brought forward on the basis of analyzing the influences of complexity, distortion and encoding bit-rate of coding parameters in the motion estimation module synthetically. And taking account of the characteristics of integer transform, quant and zig-zag scan in H.264, a complexity scalable DCT arithmetic has been produced based on the DCT pruning thought. A complexity scalable video coding framework based on parameters has been produced for the JM_OPT by taking the two above algorithms into account synthetically, which can realize the complexity scalability by adjusting its complexity control parameters, thereby a good balance between the video quality and complexity can be formed.
On this foundation, this paper proposes an optimized complexity distribution algorithm among frames and a complexity-rate combined control strategy according to the features of complexity control and rate control. And a complexity-distortion model is established, which can adjust the computational complexity adaptively according to the change of calculation capability or power consumption of terminal processor.
Finally, simulations for the C-D model are carried out in the smart phone simulator on the thought of the calculation capability, memory and energy consumption of smart phone, and the results validate the feasibility of this model.
然而,H.264的高压缩效率是以高计算复杂度为代价的,其高度的计算复杂性已造成软硬件实现的瓶颈,因此建立低复杂度的视频编码器就显得尤为重要;另外在软件编解码情况下,可利用的处理器资源随不同平台或占用该资源的任务数量而变化,要求计算复杂度不再固定。在以电池为驱动的手持终端上,考虑到功耗问题,也要求编码复杂度随时可控。目前,面向H.264开展快速编码算法研究以及复杂度-失真研究已成为业界和学术界关注的热点。本文针对这两方面开展了以下创新性研究:
首先,对于H.264参考编码器JM中比较耗时的帧间模式选择和运动估计模块,本文分别提出了自适应的帧间模式选择算法和多参考帧快速选择算法,并在此基础上对JM进行了局部代码优化,建立了低复杂度的视频编码器JM_OPT。
其次,综合分析运动估计模块各编码参数对复杂度、失真和编码比特率的影响,针对JM_OPT提出了复杂度可分级的运动估计算法;考虑H.264整数变换、量化和Zig-zag扫描的特点,基于DCT截断思想提出了复杂度可分级的DCT算法。通过对这两种算法进行综合考虑,针对JM_OPT建立了基于参数的复杂度可分级的视频编码框架,通过调节复杂度控制参数即可实现复杂度的可分级性,从而在视频质量和复杂度间形成良好折中。
在此基础上,针对复杂度控制和码率控制的特点,本文提出了帧间复杂度最优分配算法以及复杂度-速率联合控制策略,建立了复杂度-失真模型,该模型能根据终端处理器的计算能力或者功耗的变化自适应进行计算复杂度的调整。考虑智能手机在计算能力、内存和功耗等方面的特点,本文最后在智能手机模拟器上对复杂度-失真模型进行了仿真,实验结果验证了该模型的可行性。
With the economic development and technological progress, the market has increasing demands of high-performance video service. In this case, the previous video coding standards can’t meet the requirement. In 2003, the ITU-T VCEG and the ISO/IEC MPEG jointly developed a new generation video coding standard H.264/AVC, which has higher compression efficiency and improved network adaptation. Hence it will have a broad application in digital video communication and storage areas in the future.
However, the high compression efficiency of H.264 is at the cost of high computational complexity, which has become the bottleneck in the realization of software and hardware, therefore it is very important to develop a low complexity video encoder. Furthermore, in the condition of software coding and decoding, the available processor resource will change with the different platforms or assignment quantities occupying the processor resource, which requests that the encoder has unfixed computational complexity. The handset drived by the battery also requires that the coding complexity can be controlled considering the limited power consumption. Currently,the research on fast coding algorithms and complexity- distortion for H.264 have been one of the hotspot issues in both industry and academia. The following creative studies are performed according to the two aspects:
Firstly, for the time-consuming modules of inter-frame mode selection and motion estimation in H.264 reference encoder JM, an adaptive inter-frame mode decision algorithm and a multi-reference frames fast selection algorithm are proposed respectively in this paper. On the basis, local codes of JM are optimized and a low complexity video encoder JM_OPT is developed.
Secondly, a complexity scalable motion estimation arithmetic aimed at JM_OPT is brought forward on the basis of analyzing the influences of complexity, distortion and encoding bit-rate of coding parameters in the motion estimation module synthetically. And taking account of the characteristics of integer transform, quant and zig-zag scan in H.264, a complexity scalable DCT arithmetic has been produced based on the DCT pruning thought. A complexity scalable video coding framework based on parameters has been produced for the JM_OPT by taking the two above algorithms into account synthetically, which can realize the complexity scalability by adjusting its complexity control parameters, thereby a good balance between the video quality and complexity can be formed.
On this foundation, this paper proposes an optimized complexity distribution algorithm among frames and a complexity-rate combined control strategy according to the features of complexity control and rate control. And a complexity-distortion model is established, which can adjust the computational complexity adaptively according to the change of calculation capability or power consumption of terminal processor.
Finally, simulations for the C-D model are carried out in the smart phone simulator on the thought of the calculation capability, memory and energy consumption of smart phone, and the results validate the feasibility of this model.
引文
[1] Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG, Draft ITU-T recommendation and final draft international standard of joint video specification (ITU-T Rec. H.264//IEC 14496-10 AVC), Doc. G050r1, Mar.2003
[2] ITU-T. Recommendation H.263, Video coding for low bit rate communication, 1996
[3] ITU-T. Recommendation H.261, Video codec for audiovisual services at p×64Kb, March 1993
[4] ITU-T. Recommendation H.262, Information technology-generic coding of moving pictures and associated audio information: Video, 1995
[5] ITU-T. Recommendation H.263 version 2, Video coding for low bit rate communication, 1998
[6] ITU-T. Recommendation H.263 version 3, Video coding for low bit rate communication, 2000
[7] ISO/IEC IS 11172, Information technology-coding of moving pictures and associated audio for digital storage media at up to about 1.5 Mbits/s, 1993 (MPEG-1)
[8] ISO/IEC IS 13818-2, Information technology-generic coding of moving pictures and associated audio information-Part 2: Video, 1995 (MPEG-2 Video)
[9] ISO/IEC IS 14496-2, Information technology-coding of audio-visual objects-Part 2: Visual, 1999 (MPEG-4 Video)
[10] ITU-T and ISO/IEC JTC1, Scalable video coding working draft 3, JVT-P201, Jul.2005
[11] 高文,黄铁军,信源编码标准 AVS 及其在数字电视中的应用[J],电视技术,2003, (11): 4~6
[12] 中华人民共和国国家质量监督检验检疫总局、中国国家标准化管理委员会, GB/T 20090.2-2006,信息技术先进音视频编码,第 2 部分:视频[S],中华人民共和国国家标准,北京:中国标准出版社,2006
[13] T.Wiegand, G. Sullivan, G. Bjontegaard, A. Luthra, Overview of the H.264 /AVC Video Coding Standard[J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 560~576
[14] T.Stockhammer, M.M.Hannuksela and T.Wiegand, H.264/AVC in wireless environments [J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 657~673
[15] Antonio Ortega, Kannan Ramchandran, Rate-distortion methods for image and video compression[J], IEEE Signal Processing Magazine, 1998, 15(6): 23~50
[16] 朱雪龙,应用信息论基础,北京:清华大学出版社,2000
[17] Mihaela van der Schaar, T. Deepak and A. Venkatesh, Rate-distortion-complexity adaptive video compression and streaming [C], International Conference on Image Processing, ICIP2004: 2051~2054
[18] A. Church, An unsolvable problem of elementary number theory [J], American Journal of Mathematics, 1936, 58: 345~363
[19] A. Turing, On computable numbers, with an application to the entscheidungs problem, Proceedings of the London Mathematical Society, 1937, 42: 230-265. Correction: 43: 544~546
[20] A.N. Kolmogorov, Three approaches to the definition of the concept quantity of information [J], IEEE Transaction on Information Theory, 1965, 14: 662-669
[21] G.J. Chaitin, On the length of program for computing finite binary sequences[J], Journal of the Association of Computing Machinery, 1966, 13:547~569
[22] R.J. Solomonoff, A formal theory of inductive inference [J], Information and Control, June 1964, 7(2): 224~254
[23] Sophie Laplante, Kolmogorov techniques in computational complexity theory, Doctor Dissertation, 1997
[24] T. Koga, K. Iinuma, A. Hirano et al, Motion compensated interframe coding for video conferencing [C], Proceedings of the National Telecommunications Conference, New Orleans, 1981: G5.3.1~G5.3.5
[25] R. Li, B. Zeng and M.L. Liou, A new three-step search algorithm for block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, August 1994, 4(4): 428~443
[26] L. M. Po and W. C. Ma, A novel four-step search algorithm for fast block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, June 1996, 6: 313~317
[27] S. Zhu and K.K. Ma, A new diamond search algorithm for fast block matching motion estimation [J]. IEEE Transactions on Image Processing, 2000, 9(2): 287~290
[28] C. Zhu, X. Lin, L.Chau et al, Hexagon-based search pattern for fast block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, 2002, 12(5): 349~355.
[29] Z.B. Chen, P. Zhou, Y. He, Fast motion estimation for JVT, Document JVT-G016, JVT7th meeting, Pattaya, Thailand, March 2003
[30] Y.W. Huang, B.Y. Hsieh, S.Y. Chien, et al, Analysis and complexity reduction of multiple reference frames motion estimation in H.264/AVC [J], IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(4): 507~522
[31] Hyungjoon Kim, Yucel Altunbasak, Low-complexity macroblock mode selecteion for H.264/AVC encoders [C], Conferences on Image Processing, Singapore, 2004, 2: 765~768
[32] F. Pan, L. Xiao, Fast mode decision for intra prediction, ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, JVT7th Meeting, Pattaya Ⅱ, Thailand, March 2003
[33] C.S. Kim, H.H. Shih and C.C. Jay Kuo, Feature-based intra-prediction mode decision for H.264 [C], 2004 International Conference on Image Processing, 2004: 769~772
[34] Byeungwoo Jeon, Jeyun Lee, Fast mode decision for H.264, JVT-3033, Waikoloa, Hawaii, USA, 2003
[35] I. Richardson and Y. Zhao, Video encoder complexity reduction by estimating skip mode [C], Conference on Image Processing, Singapore, 2004, 1: 103~106
[36] D. M. Sow, A. Eleftheriadis,.Complexity distortion theory, IEEE International Symposium on Information Theory, 1997: 188
[37] D. M. Sow, A. Eleftheriadis. Complexity distortion theory [J], IEEE Transactions on Information Theory, 2003, 49(3): 604~608
[38] S.K. Leung-Yan-Cheong and T.M. Cover, Some equivalence between Shannon entropy and Kolmogorov complexity, IEEE Transaction on Information Theory, May 1978, IT-24: 331~339
[39] Pol Lin Tai, Chii Tung Liu, Jia Shung Wang, Complexity-adaptive search algorithm for block motion estimation [C], IEEE International Conference on Image Processing, 2001, 2: 969~972
[40] Yi Xiaoquan, Nam Ling, Scalable complexity-distortion model for fast motion estimation, Proceedings of the International Society for Optical Engineering, 2005, 5960(3): 1343~1353
[41] Lengwehasatit, A. Ortega, Rate-complexity-distortion optimization for quadtree- based DCT coding. IEEE International Conference on Image Processing, 2000, 3: 821~824
[42] Ismaeil R. Ismaeil, Computation-distortion optimized DCT-based video coding, Doctor Dissertation, The university of British Columbia, May 2000
[43] Zhihai He , Yongfang Liang, I. Ahmad, Power-rate-distortion analysis for wireless video encoding under energy constraint. Proceedings of the SPIE - The International Society for Optical Engineering, 2004, 5308(1): 57~68
[44] J.R. Lorch, A.J. Smith, Improving dynamic voltagge scaling algorithms with PACE [C], Proceedings of the 2001 ACM SIGMETRICS Conference, 2001: 50~61
[45] Joint Video Team Reference software, http://bs.hhi.de/~suehring/tml/download/
[46] T. Wiegand and B. Girod, Lagrangian multiplier selection in hybrid video coder control [C], Proceedings of the IEEE International Conference on Image Processing, Thessaloniki, Greece, Oct. 2001, 4: 221~232
[47] T. Wiegand, H. Schwarz, et al, Rate-constrained coder control and comparison of video coding standards [J], IEEE Transaction on Circuits and System for Video Technology, 2003, 13(7): 688~703
[48] J. Lee and B. Jeon, Pruned mode decision based on variable block sizes motion compensation for H.264, Multimedia Interactive Protocols and Systems (MIPS), Nov. 2003
[49] X. Jing, L.P. Chau, Fast approach for H.264 inter mode decision [J], Electronics Letters, 2004, 14(7): 1050~1052
[50] Andy C Yu, Efficient block-size selection algorithm for inter-frame coding in H.264/AVC [C], IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Canada, 2004: 169~172
[51] 段大高,崔岩松,邓中亮,H.264 的帧间宏块模式选择算法[J],现代有线传输, 2004, 3: 77~79
[52] 朱冬冬,戴琼海,H.264 快速帧间模式选择算法[J],有线电视技术,2004, 9(153): 36~40
[53] Zhang Shufang, Li Hua, Zhang Tao, A fast mode decision algorithm for h.264 inter prediction [C], 25th PCS Proceedings: Picture Coding Symposium 2006, PCS2006
[54] D. Wu, S. Wu, and Lim,Block inter mode decision for fast encoding of H.264 [C]. 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, 3: 181~184
[55] Gary Sullivan, Recommended simulation common conditions for H.26L coding efficiency experiments on low resolution progressive scan source material, VCEG-N81, the 14th meeting: Santa Barbara, CA, USA, September 24~27, 2001
[56] Zhu Hong, Wu Cheng-ke, Wang Yang-li, Fast Mode Decision for H.264/AVC based on Macroblock Correlation [C], Proceedings of the 19th International Conference on Advanced Informaiton Networking and Applications, 2005
[57] 张春田,苏育挺,张静,数字图像压缩编码,北京:清华大学出版社,2006
[58] V. Lappalainen, A. Hallapuro, T.D. Hamalainen, Performance of H.26L video encoder on general-purpose processor[J], Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, July 2003, 34(3): 239~249
[59] M. Flierl, T. Wiegand, and B. Girod, Rate-constrained multi-hypothesis motion-compensated prediction for video coding [C], Proceedings of International Conference on Image Processing, Vancouver, BC, Canada, 2000, 3: 150~153
[60] C.K. Chiang and S.H. Lai, Fast multi-reference frame motion estimation via downhill simplex search [C], IEEE International Conference on Multimedia and Expo, ICME2006: 121~124
[61] H.J. Li, C.T. Hsu and M.J. Chen, Fast multiple reference frame selection method for motion estimation in JVT/H.264 [C], the 2004 IEEE Asia-Pacific Conference on Circuits and Systems, December 6~9, 2004: 605~608
[62] 滕国伟,张兆扬,张一钧,一种基于 H.264/AVC 的多参考帧快速选择算法[J],四川大学学报(工程科学版),2005, 37(4): 100~103
[63] H. Chung, D. Romacho, A. Ortega, Fast long-term motion estimation for H.264 using multiresolution search [C], IEEE International Conference on Image Processing, Barcelona: Institute of Electrical and Electronics Engineers Computer Society, 2003: 905~908
[64] C.W. Ting, L.M. Po and C.H. Cheung, Center-biased frame selection algorithms for fast multi-frame motion Estimation in H.264 [C], Internaional Conference on Neural Networks and Signal Processing, Nanjing: CASS, 2003, 2: 1258~1261
[65] Y. Su and M.T. Sun, Fast multiple reference frame motion estimation for H.264/AVC [J], IEEE Transaction on Circuits and System for Video Technology, 2006, 3: 447~452
[66] J. Youn and M.T. Sun, A fast motion vector composition method for temporal transcoding, Proceedings of IEEE International Symposium on Circuits and Systems, 1999
[67] 何振亚,邹采荣,骆立俊,一种用于视频编码的块运动估计算法[J],电子学报,1999, 1(27): 32~36
[68] Intel Corporation, Help for VTune(TM) performance analyzer, USA: Intel Corp, 2003
[69] J. Ostermann, J. Bormans, P. List, et al, Video Coding with H.264/AVC: tools, performance, and complexity [J], IEEE Transactions on Circuits and Systems Magazine,2004, 4(1): 7~28
[70] C. Hentschel, R.Braspenning and M. Gabrani, Scalable algorithm for media processing [C], Proceedings of International Conference on Image Processing, Singapore, 2001: 342~345
[71] Zhi Yang, Haixiang Zhang, Jiajun Bu, et al, Complexity-controllable motion estimation for real-time video encoder [C], International Conference on Image Analysis and Recognition (ICIAR) 2005, 3656: 1266~1273
[72] K. Lengwehasatit, A. Ortega, A. Basso, et al, A novel computationally scalable algorithm for motion estimation [C], Proceedings on SPIE International Conference on Visual Communications and Image Processing (VCIP), 1998: 68~79
[73] R. Braspenning and G. de Haan, Effcient motion estimation with content- adaptive resolution [C], Proceedings of International Symposium on Consumer Electronics (ISCE), September 2002: E29~E34
[74] Z.M. Lu and H. Pei, Equal-average equal-variance nearest neighbor search algorithm based on Hadamard transform [C], International Conference on Machine Learning and Cybernetics, 2003, 5: 2976~2978
[75] Y.L. Chan, Wan-Chi Siu, An adaptive partial distortion search for block motion estimation [C], IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2003, 3: 153~156
[76] 张淑芳,李华,基于 H.264 的复杂度-失真最优的运动估计算法,计算机工程,2007, 33(9): 228~230
[77] 马小虎,张明敏,严华明,多媒体数据压缩标准及实现,北京:清华大学出版社,1996
[78] N. Ahmed, T. Natarajan and K.R. Rao, Discrete cosine transform [J], IEEE Transactions on Computer, 1974, C-23: 90~93
[79] W. A. Chen, C. Harrison, S. C. Fralick, A Fast computational algorithm for the discrete cosine transform [J], IEEE Transactions on Communications, 1977, COM-25(9): 1004~1011
[80] 陈禾,毛志刚,叶以正,DCT 快速算法及其 VLSI 实现[J],信号处理,1998,14: 62~70
[81] M. Vetterliand and H.J. Nussbaumer, Simple FFT and DCT algorithms with reduced number of operations [J], Signal Processing, 1984, 16: 267~278
[82] 朱跃生,马维祯,利用快速 W 变换计算离散 sine 变换及离散 cosine 变换[J],数据采集与处理, 1990, 5(3): 9~12
[83] B.G. Lee, A new algorithm to compute the discrete consine transform [C], IEEE Transactions on Acoustics, Speech, and Signal Processing, 1984, ASSP-32(6): 1243~1245
[84] N.L. Cho and S.U. Lee, Fast algorithm and implementation of 2-D discrete cosine transform [J], IEEE Transactions on Circuits and Systems, 1991, 38(3): 297~305
[85] Z. Wang, Pruning the fast discrete cosine transform [J], IEEE Transactions on Communications, 1991, 39(5): 640~643
[86] A.N. Skodras, Fast discrete cosine transform pruning [J], IEEE Transactions on signal processing, 1994, 42(7): 1833~1837
[87] H.S. Malvar, A. Hallapuro and M. Karczewicz, Low-complexity transform and quantization in H.264/AVC [J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 598~602
[88] 楼剑,陆亮,虞露,H.264 变换和量化的分析[J],浙江大学学报 (工学版),2004, 38(5): 566~570
[89] K. Lengwehasatit and A.Ortega, Scalable variable complexity approximate forward DCT [J], IEEE Transactions on Circuits and System for Video Technology, 2004, 14(11):1236~1248
[90] 张冬明,林守勋,沈燕飞,基于 H.264 的复杂度可分级的 DCT 算法[J],计算机辅助设计与图形学学报,2006, 18(8): 1250~1256
[91] C.E. Shannon, A mathematical theory of communication [J], Bell System Technical Journal, July and October, 1948, 27: 379~423 and 623~656
[92] C.E. Shannon, Coding theorems for a discrete source with a fidelity criterion [J]. IRE National Convention Record, 1959, 7(4): 142~163
[93] T. Berger, Rate distortion theory, Prentice Hall, Engle wood Cliffs, New Jersey, 1971
[94] 曲炜,朱诗兵,信息论基础及应用,北京:清华大学出版社,2005
[95] 傅祖芸,信息论—基础理论与应用,北京:电子工业出版社,2001.8
[96] G. J. Sullivan and T. Wiegand, Rate-distortion optimization for video compression [J]. IEEE Signal Processing Magazine, 1998, 15(6): 74~90
[97] L-J Lin, A. Ortega, Bit-rate control using piecewise approximated rate-distortion characteristics[J]. IEEE Transactions on Image Processing, 1998, 8(4): 446~459
[98] Iain E. G. Richardson, Video codec design: developing image and video compression systems [M]. U.S: John Wiley & Sons, 2002: 211~233
[99] H. Everett, Generalized lagrange multiplier method for solving problems of optimum allocation of resources [J], Operations Researchs, 1963, 11: 399~417
[100] V.K. Goyal and M. Vetterli, Computation-distortion characteristics of block transform coding [C], 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP97, 1997, 4: 2729~2732
[101] Mihaela van der Schaar and Y. Andreopoulos, Rate-distortion-complexity modeling for network and receiver aware adaptation [J], IEEE Transactions on Multimedia, 2005, 7(3): 471~479
[102] D. Kwon, P. Agathoklis and P. Driessen, Performance and computational complexity optimization in a configurable video coding system [C], 2003 IEEE Wireless Communications and Networking Conference Record, 2003, 3: 2086~2089
[103] W. Pan and A. Ortega, Complexity-scalable transform coding using variable complexity algorithms [C], Data Compression Conference Proceedings, 2000: 263~272
[104] R. Min, T. Furrer, and A. Chandrakasan, Dynamic voltage scaling techniques for distributed microsensor networks[C], Proceedings of IEEE Computer Society Annual Workshop on VLSI, Orlando, Florida, 2000: 43~46
[105] T.D. Burd and R.W. Brodersen, Energy efficient CMOS microprocessor design [CJ]. Proceedings of the HICSS Conference, Maui, Hawaii, 1995: 288~297
[106] AMD Incorporation, AMD PowerNow! TM technology platform design guide for embedded processors. http://www.amd.com/epd/processors
[107] Intel Incorporation, Intel XScale technology overview, http://www.intel.com/design/intelxscale
[108] P.L. Tai, S.Y. Huang and C.T. Liu, Computation-aware scheme for software-based block motion estimation [J], IEEE Transaction on Circuits and System for Video Technology, 2003, 13(9): 901~913
[109] 卢燕飞,尉明明,蒋笑冰,压缩视频通信,北京:科学出版社, 2004:57~92
[110] A. Dagiuklas and M. Ghanbari, Preventive flow control method for packet video [C], IEE Proceedings: Communications, 1996, 143(2): 98~104
[111] Test Model Editing Committee, MPEG-2 test model 5 document, http://www.mpeg.org/MPEG/MSSG/tm5
[112] R.C. Jordi and L. Shawmin, Rate control for low-delay video communications, ITU-T/SG16, Q15-A-20, Portland, 1997
[113] T. Chiang and Y. Zhang, A new rate control scheme using quadratic rate distortion model [J], IEEE Transaction Trans on Circuits and Systems for Video Technology, 1997,7(1): 287~311
[114] S.W. Ma, W. Gao and L. Yan, Proposed draft description of rate control on JVT standard, JVT-F086, JVT6th meeting, Await, Japan, 2002
[115] Z.G. Li, F. Pan, K.P. Lim, et al. Adaptive basic unit layer rate control for JVT, Document JVT-G012[A], In:7th JVT meeting[C], Pattaya,Thailand, March 2003
[116] S.W. Ma, F. Wu and Z. Li, Proposed draft of adaptive rate control, JVT-H017, JVT8th Meeting, Geneva, Switerland, 2003
[117] S.W. Ma, W. Gao and F. Wu, Rate control for JVT video coding scheme with HRO considerations, Proceedings International Conference on Image and Processing, Spain, 2003: 793~796
[118] 郭娜,智能手机发展趋势分析:跻身主流催熟 3G,电脑知识与技术:网络文化,2004, 12M: 5~6
[119] J. Tierno and C. Campo, Smart camera phones: Limits and applications [J], IEEE Pervasive Computing, April/June, 2005, 4(2): 84~87
[120] P. Zheng, L.M. Ni, Spotlight: The rise of the smart phone, IEEE Distributed Systems Online, March, 2006, 7(3): 31~44
[121] 黄再华,智能手机操作系统有哪些[J],现代计算机,2006, 6: 103
[122] 刘彦博,胡砚,马骐,Windows Mobile 平台应用与开发,北京:人民邮电出版社,2006.1~10
[123] 傅曦, 齐宇,Windows Mobile 手机应用开发,人民邮电出版社,2005.1~398
[2] ITU-T. Recommendation H.263, Video coding for low bit rate communication, 1996
[3] ITU-T. Recommendation H.261, Video codec for audiovisual services at p×64Kb, March 1993
[4] ITU-T. Recommendation H.262, Information technology-generic coding of moving pictures and associated audio information: Video, 1995
[5] ITU-T. Recommendation H.263 version 2, Video coding for low bit rate communication, 1998
[6] ITU-T. Recommendation H.263 version 3, Video coding for low bit rate communication, 2000
[7] ISO/IEC IS 11172, Information technology-coding of moving pictures and associated audio for digital storage media at up to about 1.5 Mbits/s, 1993 (MPEG-1)
[8] ISO/IEC IS 13818-2, Information technology-generic coding of moving pictures and associated audio information-Part 2: Video, 1995 (MPEG-2 Video)
[9] ISO/IEC IS 14496-2, Information technology-coding of audio-visual objects-Part 2: Visual, 1999 (MPEG-4 Video)
[10] ITU-T and ISO/IEC JTC1, Scalable video coding working draft 3, JVT-P201, Jul.2005
[11] 高文,黄铁军,信源编码标准 AVS 及其在数字电视中的应用[J],电视技术,2003, (11): 4~6
[12] 中华人民共和国国家质量监督检验检疫总局、中国国家标准化管理委员会, GB/T 20090.2-2006,信息技术先进音视频编码,第 2 部分:视频[S],中华人民共和国国家标准,北京:中国标准出版社,2006
[13] T.Wiegand, G. Sullivan, G. Bjontegaard, A. Luthra, Overview of the H.264 /AVC Video Coding Standard[J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 560~576
[14] T.Stockhammer, M.M.Hannuksela and T.Wiegand, H.264/AVC in wireless environments [J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 657~673
[15] Antonio Ortega, Kannan Ramchandran, Rate-distortion methods for image and video compression[J], IEEE Signal Processing Magazine, 1998, 15(6): 23~50
[16] 朱雪龙,应用信息论基础,北京:清华大学出版社,2000
[17] Mihaela van der Schaar, T. Deepak and A. Venkatesh, Rate-distortion-complexity adaptive video compression and streaming [C], International Conference on Image Processing, ICIP2004: 2051~2054
[18] A. Church, An unsolvable problem of elementary number theory [J], American Journal of Mathematics, 1936, 58: 345~363
[19] A. Turing, On computable numbers, with an application to the entscheidungs problem, Proceedings of the London Mathematical Society, 1937, 42: 230-265. Correction: 43: 544~546
[20] A.N. Kolmogorov, Three approaches to the definition of the concept quantity of information [J], IEEE Transaction on Information Theory, 1965, 14: 662-669
[21] G.J. Chaitin, On the length of program for computing finite binary sequences[J], Journal of the Association of Computing Machinery, 1966, 13:547~569
[22] R.J. Solomonoff, A formal theory of inductive inference [J], Information and Control, June 1964, 7(2): 224~254
[23] Sophie Laplante, Kolmogorov techniques in computational complexity theory, Doctor Dissertation, 1997
[24] T. Koga, K. Iinuma, A. Hirano et al, Motion compensated interframe coding for video conferencing [C], Proceedings of the National Telecommunications Conference, New Orleans, 1981: G5.3.1~G5.3.5
[25] R. Li, B. Zeng and M.L. Liou, A new three-step search algorithm for block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, August 1994, 4(4): 428~443
[26] L. M. Po and W. C. Ma, A novel four-step search algorithm for fast block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, June 1996, 6: 313~317
[27] S. Zhu and K.K. Ma, A new diamond search algorithm for fast block matching motion estimation [J]. IEEE Transactions on Image Processing, 2000, 9(2): 287~290
[28] C. Zhu, X. Lin, L.Chau et al, Hexagon-based search pattern for fast block motion estimation [J], IEEE Transactions on Circuits and Systems for Video Technology, 2002, 12(5): 349~355.
[29] Z.B. Chen, P. Zhou, Y. He, Fast motion estimation for JVT, Document JVT-G016, JVT7th meeting, Pattaya, Thailand, March 2003
[30] Y.W. Huang, B.Y. Hsieh, S.Y. Chien, et al, Analysis and complexity reduction of multiple reference frames motion estimation in H.264/AVC [J], IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(4): 507~522
[31] Hyungjoon Kim, Yucel Altunbasak, Low-complexity macroblock mode selecteion for H.264/AVC encoders [C], Conferences on Image Processing, Singapore, 2004, 2: 765~768
[32] F. Pan, L. Xiao, Fast mode decision for intra prediction, ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, JVT7th Meeting, Pattaya Ⅱ, Thailand, March 2003
[33] C.S. Kim, H.H. Shih and C.C. Jay Kuo, Feature-based intra-prediction mode decision for H.264 [C], 2004 International Conference on Image Processing, 2004: 769~772
[34] Byeungwoo Jeon, Jeyun Lee, Fast mode decision for H.264, JVT-3033, Waikoloa, Hawaii, USA, 2003
[35] I. Richardson and Y. Zhao, Video encoder complexity reduction by estimating skip mode [C], Conference on Image Processing, Singapore, 2004, 1: 103~106
[36] D. M. Sow, A. Eleftheriadis,.Complexity distortion theory, IEEE International Symposium on Information Theory, 1997: 188
[37] D. M. Sow, A. Eleftheriadis. Complexity distortion theory [J], IEEE Transactions on Information Theory, 2003, 49(3): 604~608
[38] S.K. Leung-Yan-Cheong and T.M. Cover, Some equivalence between Shannon entropy and Kolmogorov complexity, IEEE Transaction on Information Theory, May 1978, IT-24: 331~339
[39] Pol Lin Tai, Chii Tung Liu, Jia Shung Wang, Complexity-adaptive search algorithm for block motion estimation [C], IEEE International Conference on Image Processing, 2001, 2: 969~972
[40] Yi Xiaoquan, Nam Ling, Scalable complexity-distortion model for fast motion estimation, Proceedings of the International Society for Optical Engineering, 2005, 5960(3): 1343~1353
[41] Lengwehasatit, A. Ortega, Rate-complexity-distortion optimization for quadtree- based DCT coding. IEEE International Conference on Image Processing, 2000, 3: 821~824
[42] Ismaeil R. Ismaeil, Computation-distortion optimized DCT-based video coding, Doctor Dissertation, The university of British Columbia, May 2000
[43] Zhihai He , Yongfang Liang, I. Ahmad, Power-rate-distortion analysis for wireless video encoding under energy constraint. Proceedings of the SPIE - The International Society for Optical Engineering, 2004, 5308(1): 57~68
[44] J.R. Lorch, A.J. Smith, Improving dynamic voltagge scaling algorithms with PACE [C], Proceedings of the 2001 ACM SIGMETRICS Conference, 2001: 50~61
[45] Joint Video Team Reference software, http://bs.hhi.de/~suehring/tml/download/
[46] T. Wiegand and B. Girod, Lagrangian multiplier selection in hybrid video coder control [C], Proceedings of the IEEE International Conference on Image Processing, Thessaloniki, Greece, Oct. 2001, 4: 221~232
[47] T. Wiegand, H. Schwarz, et al, Rate-constrained coder control and comparison of video coding standards [J], IEEE Transaction on Circuits and System for Video Technology, 2003, 13(7): 688~703
[48] J. Lee and B. Jeon, Pruned mode decision based on variable block sizes motion compensation for H.264, Multimedia Interactive Protocols and Systems (MIPS), Nov. 2003
[49] X. Jing, L.P. Chau, Fast approach for H.264 inter mode decision [J], Electronics Letters, 2004, 14(7): 1050~1052
[50] Andy C Yu, Efficient block-size selection algorithm for inter-frame coding in H.264/AVC [C], IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Canada, 2004: 169~172
[51] 段大高,崔岩松,邓中亮,H.264 的帧间宏块模式选择算法[J],现代有线传输, 2004, 3: 77~79
[52] 朱冬冬,戴琼海,H.264 快速帧间模式选择算法[J],有线电视技术,2004, 9(153): 36~40
[53] Zhang Shufang, Li Hua, Zhang Tao, A fast mode decision algorithm for h.264 inter prediction [C], 25th PCS Proceedings: Picture Coding Symposium 2006, PCS2006
[54] D. Wu, S. Wu, and Lim,Block inter mode decision for fast encoding of H.264 [C]. 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, 3: 181~184
[55] Gary Sullivan, Recommended simulation common conditions for H.26L coding efficiency experiments on low resolution progressive scan source material, VCEG-N81, the 14th meeting: Santa Barbara, CA, USA, September 24~27, 2001
[56] Zhu Hong, Wu Cheng-ke, Wang Yang-li, Fast Mode Decision for H.264/AVC based on Macroblock Correlation [C], Proceedings of the 19th International Conference on Advanced Informaiton Networking and Applications, 2005
[57] 张春田,苏育挺,张静,数字图像压缩编码,北京:清华大学出版社,2006
[58] V. Lappalainen, A. Hallapuro, T.D. Hamalainen, Performance of H.26L video encoder on general-purpose processor[J], Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, July 2003, 34(3): 239~249
[59] M. Flierl, T. Wiegand, and B. Girod, Rate-constrained multi-hypothesis motion-compensated prediction for video coding [C], Proceedings of International Conference on Image Processing, Vancouver, BC, Canada, 2000, 3: 150~153
[60] C.K. Chiang and S.H. Lai, Fast multi-reference frame motion estimation via downhill simplex search [C], IEEE International Conference on Multimedia and Expo, ICME2006: 121~124
[61] H.J. Li, C.T. Hsu and M.J. Chen, Fast multiple reference frame selection method for motion estimation in JVT/H.264 [C], the 2004 IEEE Asia-Pacific Conference on Circuits and Systems, December 6~9, 2004: 605~608
[62] 滕国伟,张兆扬,张一钧,一种基于 H.264/AVC 的多参考帧快速选择算法[J],四川大学学报(工程科学版),2005, 37(4): 100~103
[63] H. Chung, D. Romacho, A. Ortega, Fast long-term motion estimation for H.264 using multiresolution search [C], IEEE International Conference on Image Processing, Barcelona: Institute of Electrical and Electronics Engineers Computer Society, 2003: 905~908
[64] C.W. Ting, L.M. Po and C.H. Cheung, Center-biased frame selection algorithms for fast multi-frame motion Estimation in H.264 [C], Internaional Conference on Neural Networks and Signal Processing, Nanjing: CASS, 2003, 2: 1258~1261
[65] Y. Su and M.T. Sun, Fast multiple reference frame motion estimation for H.264/AVC [J], IEEE Transaction on Circuits and System for Video Technology, 2006, 3: 447~452
[66] J. Youn and M.T. Sun, A fast motion vector composition method for temporal transcoding, Proceedings of IEEE International Symposium on Circuits and Systems, 1999
[67] 何振亚,邹采荣,骆立俊,一种用于视频编码的块运动估计算法[J],电子学报,1999, 1(27): 32~36
[68] Intel Corporation, Help for VTune(TM) performance analyzer, USA: Intel Corp, 2003
[69] J. Ostermann, J. Bormans, P. List, et al, Video Coding with H.264/AVC: tools, performance, and complexity [J], IEEE Transactions on Circuits and Systems Magazine,2004, 4(1): 7~28
[70] C. Hentschel, R.Braspenning and M. Gabrani, Scalable algorithm for media processing [C], Proceedings of International Conference on Image Processing, Singapore, 2001: 342~345
[71] Zhi Yang, Haixiang Zhang, Jiajun Bu, et al, Complexity-controllable motion estimation for real-time video encoder [C], International Conference on Image Analysis and Recognition (ICIAR) 2005, 3656: 1266~1273
[72] K. Lengwehasatit, A. Ortega, A. Basso, et al, A novel computationally scalable algorithm for motion estimation [C], Proceedings on SPIE International Conference on Visual Communications and Image Processing (VCIP), 1998: 68~79
[73] R. Braspenning and G. de Haan, Effcient motion estimation with content- adaptive resolution [C], Proceedings of International Symposium on Consumer Electronics (ISCE), September 2002: E29~E34
[74] Z.M. Lu and H. Pei, Equal-average equal-variance nearest neighbor search algorithm based on Hadamard transform [C], International Conference on Machine Learning and Cybernetics, 2003, 5: 2976~2978
[75] Y.L. Chan, Wan-Chi Siu, An adaptive partial distortion search for block motion estimation [C], IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2003, 3: 153~156
[76] 张淑芳,李华,基于 H.264 的复杂度-失真最优的运动估计算法,计算机工程,2007, 33(9): 228~230
[77] 马小虎,张明敏,严华明,多媒体数据压缩标准及实现,北京:清华大学出版社,1996
[78] N. Ahmed, T. Natarajan and K.R. Rao, Discrete cosine transform [J], IEEE Transactions on Computer, 1974, C-23: 90~93
[79] W. A. Chen, C. Harrison, S. C. Fralick, A Fast computational algorithm for the discrete cosine transform [J], IEEE Transactions on Communications, 1977, COM-25(9): 1004~1011
[80] 陈禾,毛志刚,叶以正,DCT 快速算法及其 VLSI 实现[J],信号处理,1998,14: 62~70
[81] M. Vetterliand and H.J. Nussbaumer, Simple FFT and DCT algorithms with reduced number of operations [J], Signal Processing, 1984, 16: 267~278
[82] 朱跃生,马维祯,利用快速 W 变换计算离散 sine 变换及离散 cosine 变换[J],数据采集与处理, 1990, 5(3): 9~12
[83] B.G. Lee, A new algorithm to compute the discrete consine transform [C], IEEE Transactions on Acoustics, Speech, and Signal Processing, 1984, ASSP-32(6): 1243~1245
[84] N.L. Cho and S.U. Lee, Fast algorithm and implementation of 2-D discrete cosine transform [J], IEEE Transactions on Circuits and Systems, 1991, 38(3): 297~305
[85] Z. Wang, Pruning the fast discrete cosine transform [J], IEEE Transactions on Communications, 1991, 39(5): 640~643
[86] A.N. Skodras, Fast discrete cosine transform pruning [J], IEEE Transactions on signal processing, 1994, 42(7): 1833~1837
[87] H.S. Malvar, A. Hallapuro and M. Karczewicz, Low-complexity transform and quantization in H.264/AVC [J], IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7): 598~602
[88] 楼剑,陆亮,虞露,H.264 变换和量化的分析[J],浙江大学学报 (工学版),2004, 38(5): 566~570
[89] K. Lengwehasatit and A.Ortega, Scalable variable complexity approximate forward DCT [J], IEEE Transactions on Circuits and System for Video Technology, 2004, 14(11):1236~1248
[90] 张冬明,林守勋,沈燕飞,基于 H.264 的复杂度可分级的 DCT 算法[J],计算机辅助设计与图形学学报,2006, 18(8): 1250~1256
[91] C.E. Shannon, A mathematical theory of communication [J], Bell System Technical Journal, July and October, 1948, 27: 379~423 and 623~656
[92] C.E. Shannon, Coding theorems for a discrete source with a fidelity criterion [J]. IRE National Convention Record, 1959, 7(4): 142~163
[93] T. Berger, Rate distortion theory, Prentice Hall, Engle wood Cliffs, New Jersey, 1971
[94] 曲炜,朱诗兵,信息论基础及应用,北京:清华大学出版社,2005
[95] 傅祖芸,信息论—基础理论与应用,北京:电子工业出版社,2001.8
[96] G. J. Sullivan and T. Wiegand, Rate-distortion optimization for video compression [J]. IEEE Signal Processing Magazine, 1998, 15(6): 74~90
[97] L-J Lin, A. Ortega, Bit-rate control using piecewise approximated rate-distortion characteristics[J]. IEEE Transactions on Image Processing, 1998, 8(4): 446~459
[98] Iain E. G. Richardson, Video codec design: developing image and video compression systems [M]. U.S: John Wiley & Sons, 2002: 211~233
[99] H. Everett, Generalized lagrange multiplier method for solving problems of optimum allocation of resources [J], Operations Researchs, 1963, 11: 399~417
[100] V.K. Goyal and M. Vetterli, Computation-distortion characteristics of block transform coding [C], 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP97, 1997, 4: 2729~2732
[101] Mihaela van der Schaar and Y. Andreopoulos, Rate-distortion-complexity modeling for network and receiver aware adaptation [J], IEEE Transactions on Multimedia, 2005, 7(3): 471~479
[102] D. Kwon, P. Agathoklis and P. Driessen, Performance and computational complexity optimization in a configurable video coding system [C], 2003 IEEE Wireless Communications and Networking Conference Record, 2003, 3: 2086~2089
[103] W. Pan and A. Ortega, Complexity-scalable transform coding using variable complexity algorithms [C], Data Compression Conference Proceedings, 2000: 263~272
[104] R. Min, T. Furrer, and A. Chandrakasan, Dynamic voltage scaling techniques for distributed microsensor networks[C], Proceedings of IEEE Computer Society Annual Workshop on VLSI, Orlando, Florida, 2000: 43~46
[105] T.D. Burd and R.W. Brodersen, Energy efficient CMOS microprocessor design [CJ]. Proceedings of the HICSS Conference, Maui, Hawaii, 1995: 288~297
[106] AMD Incorporation, AMD PowerNow! TM technology platform design guide for embedded processors. http://www.amd.com/epd/processors
[107] Intel Incorporation, Intel XScale technology overview, http://www.intel.com/design/intelxscale
[108] P.L. Tai, S.Y. Huang and C.T. Liu, Computation-aware scheme for software-based block motion estimation [J], IEEE Transaction on Circuits and System for Video Technology, 2003, 13(9): 901~913
[109] 卢燕飞,尉明明,蒋笑冰,压缩视频通信,北京:科学出版社, 2004:57~92
[110] A. Dagiuklas and M. Ghanbari, Preventive flow control method for packet video [C], IEE Proceedings: Communications, 1996, 143(2): 98~104
[111] Test Model Editing Committee, MPEG-2 test model 5 document, http://www.mpeg.org/MPEG/MSSG/tm5
[112] R.C. Jordi and L. Shawmin, Rate control for low-delay video communications, ITU-T/SG16, Q15-A-20, Portland, 1997
[113] T. Chiang and Y. Zhang, A new rate control scheme using quadratic rate distortion model [J], IEEE Transaction Trans on Circuits and Systems for Video Technology, 1997,7(1): 287~311
[114] S.W. Ma, W. Gao and L. Yan, Proposed draft description of rate control on JVT standard, JVT-F086, JVT6th meeting, Await, Japan, 2002
[115] Z.G. Li, F. Pan, K.P. Lim, et al. Adaptive basic unit layer rate control for JVT, Document JVT-G012[A], In:7th JVT meeting[C], Pattaya,Thailand, March 2003
[116] S.W. Ma, F. Wu and Z. Li, Proposed draft of adaptive rate control, JVT-H017, JVT8th Meeting, Geneva, Switerland, 2003
[117] S.W. Ma, W. Gao and F. Wu, Rate control for JVT video coding scheme with HRO considerations, Proceedings International Conference on Image and Processing, Spain, 2003: 793~796
[118] 郭娜,智能手机发展趋势分析:跻身主流催熟 3G,电脑知识与技术:网络文化,2004, 12M: 5~6
[119] J. Tierno and C. Campo, Smart camera phones: Limits and applications [J], IEEE Pervasive Computing, April/June, 2005, 4(2): 84~87
[120] P. Zheng, L.M. Ni, Spotlight: The rise of the smart phone, IEEE Distributed Systems Online, March, 2006, 7(3): 31~44
[121] 黄再华,智能手机操作系统有哪些[J],现代计算机,2006, 6: 103
[122] 刘彦博,胡砚,马骐,Windows Mobile 平台应用与开发,北京:人民邮电出版社,2006.1~10
[123] 傅曦, 齐宇,Windows Mobile 手机应用开发,人民邮电出版社,2005.1~398