博碩士論文 105523021 詳細資訊




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姓名 呂泓諭(Hung-Yu Lu)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱 利用支持向量機降低HEVC/SCC畫面內預測之運算複雜度研究
(Reduction of Computational Complexity for HEVC/SCC Intra Prediction with Support Vector Machine)
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摘要(中) 最新一代視訊編碼標準為高效率視頻編碼(HEVC),比先前的視訊編碼
標準有更好的編碼效率,HEVC的編碼單元採用了四分樹的編碼架構增加編
碼效能。
 畫面內預測當中,為了使預測更準確,使用了35個模式來進行預測,同時也大幅增加編碼複雜度。本篇論文提出一個應用於畫面內編碼的CU深度快速決策演算法,擷取畫面資訊以及空間上的相關性作為特徵,包含變異數、低頻交流值以及鄰近編碼單元深度資訊,並利用SVM判斷當前編碼單元是否該往下進行切割。接著我們利用RDO(Rate-Distortion Optimization)程序中各候選模式的SATD成本參數與該預測單元最小SATD成本參數比較,若其大於閥值,就刪除剩餘候選模式,藉此減少候選模式個數以達節省時間的效果。第四章我們會介紹螢幕內容編碼,隨著近年來手機、雲端裝置、遠端桌面等等的興起,螢幕內容視頻也漸漸普及,我們根據內容的特性將一個編碼單元分為自然內容或是螢幕內容,決定是否跳過螢幕內容編碼模式的決策,我們同樣會找尋幾個特徵,並利用SVM來做判斷,最後再結合快速深度及模式決策演算法,進一步節省計算複雜度。
摘要(英) High efficiency video coding (HEVC) is the latest video coding standard. The coding unit(CU) of HEVC uses a quadtree-based coding structure to increase coding performance. To improve predict more accurately, using 35 prediction modes in intra prediction. This process which is meant to improve the efficiency in HEVC intra prediction however leads to a significantly higher computational complexity. Hence, in this paper, we proposed an SVM based fast intra CU depth decision algorithm to reduce the computational complexity. We apply SVM with
features, including Variance, low-frequency AC value, and neighboring CU depth to our fast CU depth decision algorithm. In the procedure of Rate Distortion Optimization (RDO) of intra prediction, we will compare the SATD costs of all candidate modes with the smallest one. If the ratio is higher than the threshold, then we delete the modes to reduce the number of candidates for time saving.
Then we would introduce screen content coding, to diminish time consumption, the CUs can be classified into two groups, NCCU(natural content CU) and SCCU(screen content CU),according to the statistical characteristics, then we could skip screen content modes in NCCU, finally, we combine fast CU decision and fast mode decision to our screen content coding algorithm to reduce much more computational complexity.
關鍵字(中) ★ HEVC
★ 編碼單元
★ 畫面內預測
★ 支持向量機
關鍵字(英) ★ HEVC
★ Coding Unit
★ Intra Prediction
★ SVM
論文目次 第一章 緒論 1
1.1高效率視頻編碼(HEVC)簡介 1
1.2高效率視頻編碼架構 2
1.3研究動機與目的 6
1.4論文架構 6
第二章 畫面內預測介紹與文獻回顧 7
2.1 畫面內預測模式介紹 7
2.2 快速深度決策演算法回顧 12
2.3 快速模式決策演算法回顧 15
第三章 SVM應用於HEVC編碼單元(CU)之快速深度及模式決策演算法 17
3.1 支持向量機介紹 17
3.2特徵選取 22
3.2.1 變異數介紹 22
3.2.2低頻交流值(AClow)介紹 24
3.2.3 鄰近編碼單元深度資訊 27
3.3 SVM應用於編碼單元快速深度決策演算法 28
3.4 畫面內預測快速模式決策演算法 45
3.4.1畫面內預測快速模式決策簡單回顧 45
3.4.2各個參數影響門檻值之探討 46
3.4.3合併畫面內預測編碼單元深度及模式之快速決策演算法 49
第四章 螢幕內容編碼快速深度及模式演算法 55
4.1 螢幕內容編碼簡介…………………………………………………55
4.2 針對螢幕內容特性所做之快速模式決策演算法 57
4.2.1 SVM模型訓練方式及流程 57
4.2.2 特徵介紹 59
4.2.3 實驗結果及分析 67
4.3 合併快速深度決策演算法及針對HEVC之快速模式決策演算法 69
4.4 與其它文獻之演算法結果比較 73
第五章 結論與未來展望 80
參考文獻 81
參考文獻 [1] “Generic coding of moving pictures and associated audio information,” ISO/IEC 13818-2: Video (MPEG-2), May 1996.
[2] “Video coding for low bit rate communication, version 1,” ITU-T recommendation H.263, 1995.
[3] “Coding of audio-visual objects - Part 2: Visual,” in ISO/IEC 14496-2 (MPEG-4 Visual Version 1), Apr. 1999.
[4] Advanced Video Coding for Generic Audio-Visual Services, ITU-T Rec.H.264 and ISO/IEC 14496-10 (AVC), ITU-T and ISO/IEC JTC 1, May2003 (and subsequent editions).
[5] JCT-VC, “High Efficiency Video Coding (HEVC) Test Model 11(HM 11) Encoder Description”, JCTVC-L1002,JCT-VCMeeting, Incheon,Jan.2013.
[6] A. Saxena and F. C. Fernandes, “DCT/DST-Based Transform Coding or
Intra Prediction in Image/Video Coding”, IEEE Transactions on Image
Processing, vol. 22, No. 10, Oct. 2013.
[7] J. Sullivan, J.-R. Ohm, W.-J. Han and T. Wiegand, “Overview of the High Efficiency Video Coding (HEVC) Standard,” Pre-publication Draft, To Appear in IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-19, Dec. 2012.
[8] Yang Wang, Xiaopeng Fan, Liang Zhao, Siwei Ma, Debin Zhao, Wen Gao,
“A Fast intra coding algorithm for HEVC”, IEEE International Conference
on Image Processing (ICIP), 10.1109/ICIP.2014.7025836, Oct.2014
[9] Syun-Jie Cai, “Reduction of Computation Complexity for HEVC Intra Prediction with Support Vector Machine ”, Master Thesis, National Central University, Jun. 2017
[10] C. M. Fang, Y. T. Chang and W. H. Chung, “Fast Intra Mode Decision for
HEVC Based on Direction Energy Distribution,” in proceeding of
IEEE International Symposium on Consumer Electronics, Jun. 2013, pp.
61-62
[11] LIBSVM—A Library for Support Vector, Machineshttp://www.csie.ntu.edu.tw/~cjlin/libsvm/index.html
[12] LiquanShen, Zhaoyang Zhang, Ping An, “Fast CU Size Decision and Mode Decision Algorithm for HEVC Intra Coding”, IEEE Transactions on Consumer Electronics, vol. 59, no 1, Feb.2013
[13] Han-Yuan Hsu, “Low Computational Complexity, High Coding Efficiency Intra Prediction for HEVC,” Master Thesis, National Central University, Jun. 2016.
[14] Jianjun Lei, Dongyang Li, Zhaoqing Pan, Zhenyan Sun, Sam Kwong and Chunping Hou “Fast Intra Prediction Based on Content Property Analysis for Low Complexity HEVC-Based Screen Content Coding”, IEEE Transactions onbroadcasting, vol. 63, no. 1, March. 2017
[15] Fanyi Duanmu ; Zhan Ma ; Wei Wang ; Meng Xu ; Yao Wang, “A novel screen content fast transcoding framework based on statistical study and machine learning”, IEEE International Conference on Image Processing (ICIP),2016
指導教授 林銀議(Yin-Yi Lin) 審核日期 2019-1-25
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