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姓名 陳志彬(Jhih-Bin Chen) 查詢紙本館藏 畢業系所 通訊工程學系 論文名稱 資料隱藏與模式決策技術應用於H.264視訊編碼之錯誤防範機制
(An Error Resilient Scheme for H.264 Video Coding Based on Data Hiding and Mode Decision)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 雖然最新的H.264視訊編碼提供了很多錯誤防範機制,但是錯誤蔓延所造成的傷害依然很嚴重。本論文提出兩個錯誤防範機制,可以在有錯誤的通道上改善H.264的強健性。這些機制都是和H.264相容的,也就是說位元流可以被標準的解碼端正確的解出。第一個機制是最相似臨近區塊移動補償錯誤隱藏(NNEC),利用資料隱藏技術藏入移動向量最相似臨近區塊的索引到下一個slice裡。一旦解碼端沒有正確收到MB的移動向量資料,將會利用從位元流解回來最相似臨近區塊的索引來還原,錯誤隱藏效果會比沒有任何資料參考的情況下所做的錯誤隱藏好很多。
第二個所提出的機制是失真量估測模式決策(DEMD)。H.264模式決策是針對碼率失真最佳化,在運算中並沒有考慮到通道錯誤。因此H.264所選到的最佳模式,對有錯誤的環境下並不是最佳的。在所提出來的DEMD裡,會給一個封包遺失率,讓編碼端用遞迴的方式計算解碼端像素的失真量。在解碼端,重建畫面的像素失真量會包括量化失真、錯誤蔓延的錯誤和錯誤隱藏所帶來的錯誤。這些計算都會整合到碼率失真模型裡,去從每一個MB intra和inter編碼模式裡,選出最佳編碼模式。
從模擬結果來看,所提演算法的碼率失真表現在所有的實驗數據下,都較以往的機制好很多,尤其是將NNEC和DEMD整合,更能提供優異的效能。摘要(英) Although H.264 video coding standard provides several error resilience tools, the damage caused by the error propagation may still be tremendous. This thesis proposes two additional error resilience techniques that can improve the robustness of H.264 in noisy channels. Both of them are H.264 compatible, i.e., the bit streams can be decoded by a standard decoder with little or no degradation. The first technique is Nearest Neighbor motion compensated Error Concealment (NNEC) that utilizes a data hiding technique to embed the index of the neighboring block with the most similar motion vector into the bit stream, presumably the next slice. Once the decoder does not receive the correct MB data including its motion vector, it can use the nearest neighboring MB with the index extracted from the bit steam to perform much more accurate error concealment than the conventional blind motion concealment.
The second proposed technique is Distortion Estimated Mode Decision (DEMD). The mode decision in H.264, which is critical for the rate-distortion performance, does not consider the channel error in the computation. Therefore, an optimal mode selected by H.264 may not be optimal for a noisy environment. In the proposed DEMD, the encoder keeps estimating the decoder pixel distortion recursively for a given packet error rate. The overall pixel distortion of frame reconstruction at the decoding side includes the quantization error, the propagation error, and the concealment error. The estimates are integrated into a rate-distortion model for optimal switching between intra and inter coding for each MB.
By observing simulation results, the rate-distortion performances of the proposed algorithms are better than that of the conventional algorithms in all experimental cases. Specifically, the combination of NNEC/DEMD provides excellent performance.關鍵字(中) ★ 模式決策
★ 資料隱藏
★ 錯誤隱藏
★ H.264關鍵字(英) ★ data hiding
★ mode decision
★ error concealment
★ H.264論文目次 第一章 緒論 1
1.1 簡介 1
1.2 動機與目的 2
1.3 論文架構 4
第二章 H.264簡介和錯誤蔓延分析 5
2.1 資料壓縮簡介 5
2.2 視訊壓縮發展歷史 7
2.3 H. 264視訊壓縮標準簡介 10
2.3.1 整體壓縮效能改進情形 11
2.3.2 H.264架構介紹 12
2.3.2.1 網路提取層(Network Abstraction Layer) 13
2.3.2.2 H.264 Profiles 14
2.3.3 空間性預測(Intra Prediction) 18
2.3.4 時間性預測(Inter Prediction) 21
2.3.5 轉換(Transform) 29
2.3.6 量化(Quantization) 31
2.3.7 去區塊濾波器(Deblocking Filter) 32
2.3.8 亂度編碼(Entropy Coding) 35
2.4 H. 264 錯誤蔓延分析 36
2.4.1 空間性預測(Intra Prediction) 36
2.4.2 時間性預測(Inter Prediction) 39
2.4.3 去區塊濾波器(Deblocking Filter) 43
第三章 錯誤防範機制簡介 45
3.1 無迴授性之錯誤防範機制 46
3.1.1 正向錯誤更正機制(Forward Error Checking) 46
3.1.2 再同步標記機制(Resynchronization Marker) 47
3.1.3 資料分隔機制(Data Partition) 49
3.1.4 檔頭延伸碼機制(Header Extend Code) 50
3.1.5 可調性編碼機制(Scalable Coding) 51
3.1.5.1 時域可調性視訊編碼(Temporal Scalability) 51
3.1.5.2 空間可調性視訊編碼(Spatial Scalability) 52
3.1.5.3 SNR可調性視訊編碼(SNR Scalab ility) 53
3.1.6 錯誤隱藏(Error concealment) 54
3.1.6.1 Intra Frame 54
3.1.6.2 Inter Frame 56
3.2 迴授性之錯誤防範機制 58
3.2.1 自動重傳機制(Automatic Repeat reQuest) 58
3.2.2 參考畫面的選擇(Reference Picture Selection) 59
3.2.3 錯誤追蹤(Error Tracking) 62
3.3 H.264之錯誤防範機制 64
3.3.1 Parameter set structure 64
3.3.2 Redundant pictures 66
3.3.3 Flexible macroblock order 66
3.3.4 Data partitioning 67
第四章 資料隱藏與模式決策技術 69
4.1 資料隱藏應用於錯誤防範 70
4.1.1 資料隱藏方法 70
4.1.2 移動向量分析 74
4.1.3 最相似臨近錯誤隱藏演算法(NNEC) 77
4.2 模式決策 82
4.2.1 基本原理 83
4.2.2 模式決策應用之錯誤防範機制 85
4.3 整合資料隱藏與模式決策技術 87
4.3.1 修正模式決策技術中的 和 87
4.3.2 整合後的實作與流程 88
第五章 實驗結果與討論 91
5.1 環境參數設定與所使用的樣本 91
5.2 結果比較與分析 92
5.2.1 碼率失真曲線之比較 93
5.2.1.1 NNEC和JM 9.4比較 93
5.2.1.2 DEMD和RIR比較 96
5.2.1.3 DEMD&NNEC和RIR&NNEC比較 100
5.2.1.4 六種機制的比較 106
5.2.2 資料隱藏的代價 108
第六章 結論與未來展望 109
參考文獻 110參考文獻 [1]“Final committee draft: Editor’s proposed revisions,” in Joint Video Team(JVT) of ISO/IEC MPEG and ITU-T VCEG, T. Wiegand, Ed., Feb.2003,JVT-F100.
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[3]T. Wiegand, G. J.Sullian, G. Bjontegaard, and A.Luthra, “Overview of the H.264/AVC video coding standard,” IEEE Trans. Circuits Syst. Video Technol., vol. 13, pp. 560–576, July 2003.
[4]ITU-T Recommendation H.261: Video Codec for Audiovisual Services at Px64 Kbits, ITU, 1993.
[5]ISO/IEC JTC1, Generic Coding of Audiovisual Objects –Part 2: Visual (MPEG-4 Visual), ISO/IEC 14496-2, Version 1: Jan. 1999; Version 2: Jan. 2000; Version 3: Jan. 2001.
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[10] S. Fukunaga, T. Nakai. and H.Inoue, “ Error resilient video coding by dynamic replacing of reference pictures,” Proc. IEEE GLOBECOM, vol. 3, pp.1503-1508, Nov 1996.
[11]P.C. Chang and T.H. Lee, “Precise and fast error tracking for error resilient transmission of H.263 video,” IEEE Trans. Circuits Syst. Video Technol., vol.10, pp.600-607,June 2000.
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[14]J. Song, and K. J. R. Liu, “A Data Embedding Scheme for H.263 Compatible Video Coding,” ISCAS '99. Proceedings of the 1999 IEEE International Symposium on, vol. 4 , p. 390 –393, 1999.
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[16]M. K. Tsai, T. H. Lee, J. T. Wang, and P. C. Chang, "Synchronous backward error tracking algorithm for H.264 video coding," in Proc. SPIE Conf. Image and Video Communications and Processing, vol. 5685, pp. 195-202, Mar. 2005.
[17]L. W. Kang and J. J. Leou, "An error resilient coding scheme for H.264/AVC video transmission based on data embedding," J. Visual Communication and Image Representation, vol. 16, no. 1, pp. 93-114, Feb. 2005.
[18]T. Stockhammer, D. Kontopodis, and T. Wiegand, "Rate-distortion optimization for JVT/H.26L video coding in packet loss environment," in Proc. 2002 Int. Packet Video Workshop, Pittsburgh, USA, Apr. 2002.指導教授 張寶基(Pao-Chi Chang) 審核日期 2005-7-11 推文 plurk
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