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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 葉丙成 | |
dc.contributor.author | Wei-Ting Lin | en |
dc.contributor.author | 林韋廷 | zh_TW |
dc.date.accessioned | 2021-06-16T23:40:34Z | - |
dc.date.available | 2017-08-01 | |
dc.date.copyright | 2012-08-01 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-07-25 | |
dc.identifier.citation | [1] D. Slepian and J. Wolf, “Noiseless coding of correlated information sources,” Information
Theory, IEEE Transactions on, vol. 19, no. 4, pp. 471–480, 1973. [2] J. Garcia-Frias, “Compression of correlated binary sources using turbo codes,” Communications Letters, IEEE, vol. 5, no. 10, pp. 417–419, 2001. [3] F. Daneshgaran, M. Laddomada, and M. Mondin, “Iterative joint channel decoding of correlated sources employing serially concatenated convolutional codes,” Information Theory, IEEE Transactions on, vol. 51, no. 7, pp. 2721–2731, 2005. [4] H. Singh, J. Oh, C. Kweon, X. Qin, H. Shao, and C. Ngo, “A 60 GHz wireless network for enabling uncompressed video communication,” Communications Magazine, IEEE, vol. 46, no. 12, pp. 71–78, 2008. [5] S. Hong and W. Lee, “Flexible unequal error protection scheme for uncompressed video transmission over 60ghz multi-gigabit wireless system,” in Computer Communications and Networks (ICCCN), 2011 Proceedings of 20th International Conference on. IEEE, 2011, pp. 1–6. [6] G. Wallace, “The jpeg still picture compression standard,” Communications of the ACM, vol. 34, no. 4, pp. 30–44, 1991. [7] J. Proakis, “Digital communications,” 2007. [8] K. Larsen, “Short convolutional codes with maximal free distance for rates 1/2, 1/3, and 1/4 (corresp.),” Information Theory, IEEE Transactions on, vol. 19, no. 3, pp. 371–372, 1973. [9] L. Bahl, J. Cocke, F. Jelinek, and J. Raviv, “Optimal decoding of linear codes for minimizing symbol error rate (corresp.),” Information Theory, IEEE Transactions on, vol. 20, no. 2, pp. 284–287, 1974. [10] C. Berrou, A. Glavieux, and P. Thitimajshima, “Near shannon limit error-correcting coding and decoding: Turbo-codes. 1,” in Communications, 1993. ICC 93. Geneva. Technical Program, Conference Record, IEEE International Conference on, vol. 2. IEEE, 1993, pp. 1064–1070. [11] J. Hagenauer and L. Papke, “Decoding ”turbo”-codes with the soft output viterbi algorithm (sova),” in Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on. IEEE, 1994, p. 164. [12] B. Girod, A. Aaron, S. Rane, and D. Rebollo-Monedero, “Distributed video coding,” Proceedings of the IEEE, vol. 93, no. 1, pp. 71–83, 2005. [13] S. Li, Markov random field modeling in computer vision. Springer-Verlag New York, Inc., 1995. [14] J. M. Hammersley and P. Clifford, “Markov fields on finite graphs and lattices,” Unpublished manuscript, vol. 3, 1971. [Online]. Available: http: //www.citeulike.org/user/derinb/article/582378 [15] S. Ten Brink, “Convergence behavior of iteratively decoded parallel concatenated codes,” Communications, IEEE Transactions on, vol. 49, no. 10, pp. 1727–1737, 2001. [16] T. Moon, Error correction coding. Wiley Online Library, 2005. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65397 | - |
dc.description.abstract | 在影像壓縮的技術中常利用禎內預測壓縮的來避免錯誤波及到後續的畫面。
尤其是在分散視訊壓縮系統中,禎內預測的畫面更被使用於預測其他禎的畫面。 因此會有更多的畫面只使用到禎內預測。但是禎內預測的壓縮率遠低於使用禎間 預測的壓縮率,於是很多能量浪費在傳輸可以從另一張畫面預測出的資料上。我 們發現只使用禎內預測壓縮出來的資料有很高的關聯性,而這些關連性可以用來 減少所需的傳輸能量。但是這些關連性在傳統的壓縮技術中會非常的難以利用。 於是我們稍微改變了傳統的禎內壓縮,使得這些關連性變得比較好利用。另外, 由於60GH微波系統的興起,這個觀念更可以延伸到未壓縮的視訊壓縮上。我們利 用了雜訊模型以及馬可赫夫隨機場分別來描述禎與禎之間的關聯性和禎內之間像 素的關係。利用這些關連性可以使得經過通道解碼的資料錯誤率降低。因此我們 所提出的系統可以使得每個禎所需傳輸的能量相似於利用禎內壓縮所的畫面所需 的傳輸能量。這表示這個系統可以操作在非常低的信噪比下。由於60GHz這的頻 段的訊號能量遞減效應會非常大,這個系統非常適合這個頻段的視訊傳輸。此 外,由於我們提出的系統的紀錄器複雜度非常的低,非常適合監視系統以及傳輸 連續拍照這類需要低成本和低能量紀錄器的應用。 | zh_TW |
dc.description.abstract | Intra-coded frames are frequently used to prevent error propagation, and moreover, in
the distributed video coding system, the intra-coded frames is used to predict the adjacent frames. However, the bit-rate of the intra-coded frames is much more than that of the intercoded frames, which results in power waste. We find that the high correlation between the coded bitstreams of intra-coded frames can be used for channel decoding to reduce the transmission power. However the correlation is difficult to be exploited since the pixel values are encoded as logical bits. Therefore, the source encoder is modified for the channel decoder to utilize the identical data between the intra-coded frames. This concept can be extended to the uncompressed video transmissions, mainly due to the emergence of the 57-66 GHz mmWave systems. To transmit the uncompressed video power efficiently, we propose a channel decoder that utilizes both temporal and spatial redundancy among the video frames. The temporal redundancy between the frames is exploited via a correlation noise model, and the spatial redundancy inside each frame is exploited with the aid of Markov random field (MRF) model. By combining the above models and an error control code, the proposed system is more error robust. The recording devices of the proposed system is less complex than the system transmitting intra-coded frames while the PSNR performance is maintained under the same transmission power per frame comparing to the transmission of intra-coded frames. That is, the system can operate in an extremely low SNR condition which is common in mmWave frequency bands due to the signals suffer greater propagation loss. Besides, the low-cost and low power characteristics make it a perfect match for surveillance systems and the applications transmitting serially shoot images. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T23:40:34Z (GMT). No. of bitstreams: 1 ntu-101-R99942064-1.pdf: 6847211 bytes, checksum: 4786288a622de20e2652e91f8e1a0662 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 1 Introduction 1
2 Backgroud Knowledge 5 2.1 JPEG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Inter, Intra Coding and Group of Pictures Structure . . . . . . . . . . . . 6 2.3 Distributed Video Coding . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.4 Trellis Based Code Decoding Algorithm . . . . . . . . . . . . . . . . . . 8 2.4.1 Overview of Convolutional Code Encoder . . . . . . . . . . . . . 8 2.4.2 BCJR - MAP Decoding Rule . . . . . . . . . . . . . . . . . . . . 12 2.4.3 Soft Output Viterbi - MLS Decoding Rule . . . . . . . . . . . . . 14 3 Iterative Channel Decoding Using Temporal Correlation for Video Frames 17 3.1 Applying Temporal Information with Spatial Source Coding . . . . . . . 17 3.1.1 Encoder Structure . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.1.2 Decoder Structure . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.1.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2 Jointly Decoding Two Frames at Bit-Plane Levels . . . . . . . . . . . . . 25 3.2.1 Encoder and Decoder Structures . . . . . . . . . . . . . . . . . . 29 3.2.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.3 Joint Multiple Frames Decoding at Bit-Plane Levels . . . . . . . . . . . . 33 3.3.1 Decoder Structure . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.3.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 35 4 MRF Based Joint Source and Channel Decoding 37 4.1 MRF Analysis at Bit-Plane Level with LLR . . . . . . . . . . . . . . . . 38 4.2 Encoder and Decoder Structure . . . . . . . . . . . . . . . . . . . . . . . 46 4.2.1 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.3 EXIT Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.4 MRF Analysis with Wavelet Transform . . . . . . . . . . . . . . . . . . 51 4.4.1 Unequal Modulation . . . . . . . . . . . . . . . . . . . . . . . . 54 4.4.2 Encoder Structure and Decoder Structure with Wavelet Transform 56 4.4.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 56 5 Joint MRF and Temporal Correlation Decoding 59 5.1 Encoder and Decoder Structures with Wavelet Transform . . . . . . . . . 59 5.1.1 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 61 5.2 Encoder and Decoder Structures of HD Videos Transmission . . . . . . . 64 5.2.1 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 65 6 Conclusions and Future Works 67 Appendix 1 Proof of MRF with LLR 69 Bibliography 71 | |
dc.language.iso | en | |
dc.title | 利用影像時空隱含資訊的疊代式通道解碼 | zh_TW |
dc.title | Iterative Channel Decoding Using Spatial and Temporal
Intrinsic Information for Video Source | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇炫榮(Hsuan-Jung Su),魏宏宇,謝宏昀 | |
dc.subject.keyword | 疊代式通道解碼,馬可赫夫隨機場,分散式影像壓縮, | zh_TW |
dc.subject.keyword | iterative decoding,MRF model,DVC, | en |
dc.relation.page | 72 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2012-07-25 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
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