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姓名 陳建宏(Chien-Hung Chen)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱 利用半色調技術改善HEVC畫面內預測品質之研究
(HEVC Intra Prediction with Halftoning Technique)
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摘要(中) 新一代的視訊壓縮標準HEVC(High Efficiency Video Coding)畫面內預測之角度模式擁有33個不同的方向,使得預測畫面能更精確地預測,而得到更好的壓縮效能。然而HEVC角度預測擁有單一方向性的缺點,因此在複雜紋理的畫面還有改善的空間。曾有文獻[1]提出利用渲染方法來加以改善預測畫面,但編碼時間過長,為了解決此問題,文獻[2]提出了新的方法,將原本使用於半色調法(Halftoning)的錯誤擴散法(Error Diffusion)應用於畫面內預測(Intra Prediction)之中。錯誤擴散法能夠在不增加過多編碼時間的情況下,有效改善含有複雜紋理之區塊的預測畫面,進而增進壓縮的效能。但增加20%的編碼時間還是覺得太多,因此本篇論文將錯誤擴散法加以改良,讓時間下降至5%並且能夠改善編碼效能,另外半色調法裡除了有錯誤擴散法之外,還有另一個有序抖色法(Order Dithering),我們將之應用至HEVC畫面內預測,經由實驗證明,僅需增加約3%的編碼時間,且依然能夠降低約0.5%的BDBR(Bjontegaard Delta Bit Rate)。
摘要(英) In order to predict more accurately, High Efficiency Video Coding, the latest standard of video compression, has 33 different directions in intra prediction, so we can get better coding performance. However, the characteristic of single directionality has not changed. There is still plenty of room for improvement in complex texture image. To improve coding performance of intra prediction, the inpainting technique[1] has been studied but it is impractical because of its high computational complexity. In [2], Error diffusion is applied to HEVC intra prediction. It can improve the quality of prediction images by extending the information of bilateral reference pixels to them with only a little increase of time consumption. In addition, It still has 20% increase of encoding time, so we improve it in this paper. The improving error diffusion just need 5%, and the coding performance can be better. Except for the error diffusion, there is another technique named ordered dithering which come from Halftoning. We apply it to HEVC intra prediction. The results demonstrate that average 0.5% BDBR reduction can be achieved, and only need 3% increase of encoding time in the proposed algorithm, compared to HEVC intra prediction.
關鍵字(中) ★ 高效率視頻編碼
★ 畫面內預測
★ 半色調
★ 錯誤擴散法
★ 有序抖色法
關鍵字(英) ★ HEVC
★ Intra Prediction
★ Halftoning
★ Error Diffusion
★ Ordered Dithering
論文目次 章節目錄
第一章 緒論 1
1.1 高效率視訊編碼(HEVC)簡介 1
1.2 研究動機與目的 5
1.3 論文架構 5
第二章 畫面內預測介紹與文獻回顧 6
2.1 HEVC畫面內預測模式探討 6
2.2利用渲染方法改善HEVC畫面內預測論文回顧 16
2.3利用錯誤擴散法改善HEVC畫面內預測論文回顧 17
第三章 一種利用錯誤擴散法改善HEVC畫面內預測編碼 30
3.1 錯誤擴散法之改良型遮罩 31
3.2 錯誤擴散法之雙向合併 42
3.3 改良預測模式之選擇流程 51
3.4 綜合編碼效能比較 60
第四章 一種利用有序抖色法改善HEVC 畫面內預測編碼 72
4.1 有序抖色法簡介 72
4.2 有序抖色法與HEVC 畫面內預測之結合型演算法 75
4.3 綜合編碼效能分析 82
第五章 結論與未來展望 99 89
參考文獻 101
參考文獻 [1] Y. Zhang, “Improving HEVC Intra Prediction with Inpainting Method,” Master Thesis, National Central University, July 2013.
[2] Ying-Hsiu Lai and Yinyi Lin, “Error Diffused Intra Prediction for HEVC,” in Proc. ICASSP, PP. 1424-1427, April 2015.
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[5] “Video coding for low bit rate communication, version 1,” ITU-T recommendation H.263, 1995.
[6] 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).
[7] JCT-VC, “High Efficiency Video Coding (HEVC) Test Model 11(HM 11) Encoder Description”, JCTVC-L1002,JCT-VCMeeting, Incheon,Jan.2013.
[8] J. Min, S. Lee, I. Kim, W. J. Han, J. Lainema, and K. Ugur, “Unification of the directional intra prediction methods in TMuC,” JCTVC-B100, Geneva, CH, 21-28 July 2010.
[9] T. K. Tan, M. Budagavi, and J. Lainema, “Summary Report for TE5 on Simplification of Unified Intra Prediction,” JCTVC-C046, Guangzhou, China, Oct. 2010.
[10] M. Wien, “Variable block-size transform for H.264/AVC,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, No.7, 604-619, 2003.
[11] G. J. Sullivian, J. R. Ohm, W. J. Han and T. Wiegand, “Overview of the High Efficiency Video Coding(HEVC) Standard,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, Dec. 2012.
[12] M. Bertalmio, G. Sapiro, V. Caselles and C. Ballester, “Image inpainting,” in Proceedings of ACM SIGGRAPH, Jul. 2000, pp. 417-424.
[13] T. F. Chan and J. Shen, “Mathematical models for local non-texture inpainting,” SIAM Journal on Applied Mathematics, vol. 62, no. 3, pp.1019-1043, 2002.
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[15] Y. Wu, M. Wang, X. Liu, “A Fast Inpainting Algorithm Using Half-Point Gradient,” in Proceedings of IEEE Second International Workshop on Computer Science and Engineering, China, 28-30 Oct. 2009.
[16] D. Liu, X. Sun, F. Wu and etc., “Edge-oriented Uniform Intra Prediction,” IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1827-1836, Oct. 2008.
[17] D. Doshkov, P. N. Nya, H. Lakshman and etc., “Towards Efficient Intra Prediction based on Image Inpainting Method,” in Proceedings of Picture Coding Symposium, Dec. 2010, pp.470-473.
[18] X. Qi, T. Zhang, F. Ye and etc., “Intra Prediction with Enhanced Inpainting Method and Vector Prediction for HEVC”, IEEE International Conference on ICASSP, pp. 1217-1220, March 2012
[19] R. Ulichney, “A review of halftoning techniques,” Cambriddge Research Lab, Cambridge, MA 02139, USA.
[20] R. W. Floyd and L. Steinberg, “An adaptive algorithm for spatial grayscale,” in Proceedings of the Society of Information Display, 1976, vol. 17/2, pp. 75-77.
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[23] G. Bjontegarrd, “Calculation of average PSNR differences between RD curves,” in Proceedings of International Telecommunication Union SC16/Q6 13th Vedio Coding Experts Group meeting(ITU-T VCEG), Austin, TX, Apr. 2001, No.VCEG-M33.
[24] V. Ostromoukhov, “A Simple and Efficient Error-Diffusion Algorithm,” Universit´e de Montr´eal, pp.567-572
[25] Henry R. Kang, “ Digital Color Halftoning, ”Peerless Systems Corporation, 1999.
[26] Jae-Woo Ahn and Wonyong Sung, Member,“Multimedia processor-based implementation ofan error-diffusion halftoning algorithm exploitingsubword parallelism, ” Circuits and Systems for Video Technology, IEEE Transactions on, Volume:11 Issue: 2 , Feb 2001. Page(s): 129 -138
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指導教授 林銀議(Yin-Yi Lin) 審核日期 2015-8-13
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