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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 吳家麟(Ja-Ling Wu) | |
dc.contributor.author | Hsiao-Yun Tseng | en |
dc.contributor.author | 曾筱雲 | zh_TW |
dc.date.accessioned | 2021-06-15T06:46:31Z | - |
dc.date.available | 2011-07-06 | |
dc.date.copyright | 2011-07-06 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-06-18 | |
dc.identifier.citation | [1] B. Girod, A. M. Aron, S. Rane, and D. Rebollo-Monedero, 'Distributed video coding,' Proc. IEEE, vol. 93, no. 1, pp. 71-83, Jan. 2005.
[2] D. Slepian and J. Wolf, 'Noiseless coding of correlated information sources,' IEEE Transactions on Information Theory, vol. 19, no. 4, pp. 471-480, Jul. 1973. [3] A. Wyner and J. Ziv, 'The rate-distortion function for source coding with side information at the decoder,' IEEE Transactions on Information Theory, vol. 22, no. 1, pp. 1-10, Jan. 1976. [4] R. Puri and K. Ramchandran, 'PRISM: A New Robust Video Coding Architecture Based on Distributed Compression Principles,' Proc. Allerton Conf., October 2002. [5] Aaron, A.; Rui Zhang; Girod, B.; , 'Wyner-Ziv coding of motion video,' Signals, Systems and Computers, Conference Record of the Thirty-Sixth Asilomar Conference on , vol.1, no., pp. 240- 244 vol.1, 3-6 Nov. 2002. [6] X. Artigas, J. Ascenso, M. Dalai, S. Klomp, D. Kubasov, M. Ouaret, 'The DISCOVER codec: Architecture, Techniques and Evaluation,' Picture Coding Symposium 2007. [7] R. Baraniuk, 'Compressive sensing [lecture notes],' IEEE Signal Processing Magazine, vol. 24, no. 4, pp. 118-121, Jul. 2007. [8] E. J. Candes, J. Romberg, and T. Tao, 'Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,' IEEE Transactions on Information Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006. [9] D. L. Donoho, 'Compressed sensing,' IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, Apr. 2006. [10] J. Prades-Nebot, Y. Ma, and T. Huang, 'Distributed video coding using compressive sampling,' in Proc. of Picture Coding Symposium, USA, May 2009. [11] Hung-Wei Chen, Li-Wei Kang, and Chun-Shien Lu, 'Dynamic Measurement Rate Allocation for Distributed Compressive Video Sensing,' in Proc. IEEE/SPIE Visual Communications and Image Processing, July 2010. [12] R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, 'A simple proof of the restricted isometry property for random matrices,' Constructive Approximation, vol. 28, no. 3, pp. 253-263, Dec. 2008. [13] R. Berinde and P. Indyk, 'Sparse recovery using sparse random matrices,' 2008. [14] S. Ji , Y. Xue and L. Carin, 'Bayesian compressive sensing', IEEE Transaction on Signal Processing, vol. 56, p.2346 , 2008. [15] Baron, D., Sarvotham, S., Baraniuk, R.G., 'Bayesian Compressive Sensing Via Belief Propagation', IEEE Transaction on Signal Processing, vol.58, no.1, pp.269-280, Jan. 2010. [16] ISO/IEC 14496 –10 2003: Coding of audio-visual objects – part 10: advanced video coding [17] T. T. Do, Y. Chen, D. T. Nguyen, N. Nguyen, L. Gan, and T. D. Tran, 'Distributed compressed video sensing,' in Proc. of IEEE International Conference on Image Processing, Nov. 2009. [18] Ascenso, J.; Brites, C.; Pereira, F., 'Content Adaptive Wyner-ZIV Video Coding Driven by Motion Activity,' Image Processing, 2006 IEEE International Conference on , vol., no., pp.605-608, 8-11 Oct. 2006. [19] Martins, R., Brites, C., Ascenso, J., Pereira, F., 'Statistical motion learning for improved transform domain Wyner-Ziv video coding', IET-IPR, No. 1, pp. 28-41, Feb. 2010. [20] BRITES C., PEREIRA F., 'Correlation noise modeling for efficient pixel and transform domain Wyner–Ziv video coding,' IEEE Trans. Circuits Syst. Video Technol., vol. 18, no. 9., pp. 1177–1190, September, 2008. [21] Figueiredo, M.A.T.; Nowak, R.D.; Wright, S.J., 'Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems,' Selected Topics in Signal Processing, IEEE Journal of , vol.1, no.4, pp.586-597, Dec. 2007 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48113 | - |
dc.description.abstract | 隨著無線網路技術的進步與手持式行動裝置的普及,隨時隨地在任何平台上進行影像錄製、視訊播放、影像處理與影片分享已不再只是一個幻想。然而,要讓使用者即使在低功率、低運算能力的裝置上都能快速的取得、播放與分享數位影片,還有許多技術上的挑戰需要克服,例如降低感測與編碼計算所需之資源、提高壓縮的效率等等。近年來,分散式視訊編碼 (distributed video coding) 興起提供了影像壓縮新的方法。它顛覆了傳統的壓縮方式,將原本必須在編碼端大量計算的複雜度移至解碼端來做。另外,壓縮感測 (compressive sensing) 的技術,提供了將信號的壓縮與感測在同一時間完成的方法,大幅降低感測所需的成本。 在此篇論文中,我們以分散式視訊編碼結合壓縮感測技術,來降低感測與編碼計算所需之資源,並提高壓縮的效率。我們的系統以壓縮感測為基礎,探索影片空間上和時間上 (spatio-temporal) 的統計特性,做為解碼時輔助的旁消息。我們提出了藉由分析訊號的統計特性來增強旁消息 (side information) 品質的演算法,並利用旁消息計算出訊號的機率模型,做為可信度傳遞 (belief propagation) 解碼時使用的事前機率。實驗結果顯示,和現存其他以壓縮感測為基礎的方法相比,我們的方法大幅提升了訊號重建的結果。 | zh_TW |
dc.description.abstract | In this thesis, a novel distributed video coding (DVC) scheme on the basis of compressive sensing (CS) that achieves low-complexity for encoding and efficient signal sensing is presented. Most CS recovery algorithms rely only on the signal sparsity. Yet, under DVC architecture, additional statistical characterization of the signal is available, which offers the possibility of achieving more precise CS recovery. First, a set of random measurements are acquired and transmitted to the decoder. The decoder then exploits the statistical characterization of the signal and generates the side information (SI). Finally, utilizing the SI, a Bayesian inference using belief propagation (BP) decoding is performed for signal recovery. The proposed CS-DVC system offers a more direct way of signal acquisition and the potential for more precise estimation of the signal from random measurements. Experimental results indicate that the generated SI can improve the signal reconstruction quality in comparison with a CS recovery algorithm which relies only on the signal sparsity. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T06:46:31Z (GMT). No. of bitstreams: 1 ntu-100-R98922026-1.pdf: 1484901 bytes, checksum: ce0bcd1067491c96caab2265ef380d0f (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 誌謝 I
中文摘要 II ABSTRACT III CONTENTS IV LIST OF FIGURES VI LIST OF TABLES VII CHAPTER 1 INTRODUCTION 1 CHAPTER 2 RELATED WORKS 6 2.1 DISTRIBUTED VIDEO CODING 6 2.1.1 The Theoretical Foundations 6 2.1.2 Practical Schemes 7 2.2 COMPRESSIVE SENSING 8 2.2.1 Background Of Compressive Sensing 8 2.2.2 The Restricted Isometry Property 9 2.2.3 Bayesian Compressive Sensing 10 2.3 DISTRIBUTED VIDEO CODING BASE ON COMPRESSIVE SENSING 11 CHAPTER 3 CS-DVC CODEC ARCHITECTURE 13 3.1 THE BASIC IDEA 13 3.2 THE CS ENCODER 14 3.3 SIDE-INFORMATION CREATION 16 3.3.1 Frame Interpolation 16 3.3.2 Statistical Motion Field Estimation 18 3.4 THE CS DECODER 20 3.4.1 Correlation Noise Modeling 20 3.4.2 Cs-Bp Recovery 20 CHAPTER 4 PERFORMANCE EVALUATION AND DISCUSSION 22 4.1 PERFORMANCE EVALUATION CONDITIONS 22 4.1.1 Test Materials 22 4.1.2 Scenarios 23 4.1.3 Skip-Mode Selection 24 4.1.4 Benchmarks 25 4.2 SI QUALITY TEMPORAL EVOLUTION 25 4.3 PSNR TEMPORAL EVOLUTION 27 4.4 OVERALL RATE-DISTORTION PERFORMANCE 27 4.4.1 Cs-Dvc Codec Under Scenario 1 27 4.4.2 Cs-Dvc Codec Under Scenario 2 29 CHAPTER 5 CONCLUSIONS 30 REFERENCE 31 | |
dc.language.iso | en | |
dc.title | 以壓縮感測為基礎之旁消息增強分散式視訊編碼 | zh_TW |
dc.title | Side-information Enhanced Distributed Video Coding with Compressive Measurements | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳維超(Wei-Chao Chen),陳宏銘(Homer H. Chen),鄭羽伸 | |
dc.subject.keyword | 分散式視訊編碼,壓縮感測,旁消息, | zh_TW |
dc.subject.keyword | Compressive sampling,distributed video coding,side information, | en |
dc.relation.page | 33 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-06-21 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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