用於螢幕內容影像有效的內容感知彩度重建方法｜國立臺灣科技大學博碩士論文系統

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研究生：	梁晏誠 Yan-Cheng Liang
論文名稱：	用於螢幕內容影像有效的內容感知彩度重建方法 Effective Content-aware Chroma Reconstruction Method for Screen Content Images
指導教授：	鍾國亮 Kuo-Liang Chung
口試委員:	陳建中廖弘源范國清李同益鍾國亮
學位類別：	碩士 Master
系所名稱：	電資學院 - 資訊工程系 Department of Computer Science and Information Engineering
論文出版年：	2018
畢業學年度：	106
語文別：	英文
論文頁數：	26
中文關鍵詞：	彩度拷貝、內容感知彩度重建、彩度抽樣辨識、高效率視訊編碼 (HEVC) 、重建品質、螢幕內容影像 (SCI)
外文關鍵詞：	Chroma copy, Content-aware chroma reconstruction, Chroma subsampling identification, JCT-VC, Screen content image (SCI)
相關次數：	點閱：138 下載：3
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上一筆

我們提出了一個針對螢幕內容影像 (SCI) 提出一個創新有效的內容感知彩度重建方法。在用戶端得到解壓後的 YUV 影像後，首先會先將彩度平面中周圍有相同彩度值的像素利用所提的快速彩度複製法重建空缺的彩度值。這些重建的像素是位於 SCI 的平滑區。接著，針對SCI 的非平滑區，我們提出了一個基於非平坦區的快速贏家優先投票法 (NRWV) 來判斷彩度在伺服器端在壓縮前使用的彩度抽樣方式。接下來，提出了一個有效的混和方法來重建每個在非平滑區的彩度像素。針對每個空缺的像素，所提的混合方法會自適應的結合兩個彩度重建結果，一個是對於 SCI 銳利邊有較好結果的基於 NRWV 改良式亮度導引彩度重方法，另一個則是對於模糊及連續紋理有較好效果的雙三次內插法。本方法會更進一步的利用基於幾何對齊的誤差補償方法來強化重建的彩度影像。透過 26 張 SCI 標準影像及 9 部 SCV 測試影片，本方法與現存最新的彩度重建方法比較並取得最佳的品質效果改善。

In this thesis, we propose an effective novel content-aware chroma reconstruction (CACR) method for screen content images (SCIs). After receiving the decoded downsampled YUV image at the client side, firstly, a fast chroma copy approach is proposed to reconstruct each missing chroma pixel when all of its neighboring chroma pixels have the same chroma value. These reconstructed chroma pixels belong to flat regions in SCI. Secondly, for non-flat regions in SCI, a fast non-flat region-based winner-first voting (NRWV) strategy is proposed to identify the chroma subsampling scheme used at the server side, prior to compression. And then, an effective hybrid approach is proposed to reconstruct each missing chroma pixel in the non-flat region. For each missing pixel, the proposed hybrid approach adaptively fuses the two reconstructed results, one from our modiﬁed NRWV-based chroma subsampling-binding and luma-guided chroma reconstruction scheme, which favors the sharp edges in SCI, as well as the other from the bicubic interpolation scheme which favors blurred and continuous-tone textures in SCI. Further, a geometry-alignment based error compensation approach is proposed to enhance the reconstructed chroma image. Based on the 26 typical test SCIs and 9 JCT-VC test SCVs (screen content videos), thorough experiments in the HEVC reference software HM-16.17 are carried out to demonstrate the quality and quality-bitrate tradeoff merits of the proposed CACR method when compared with existing state-of-the-art methods.

指導教授推薦書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
論文口試委員審定書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii
Abstract in English. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iv
Contents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
List of Figures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .vii
List of Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Contribution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 The Proposed Content-aware Chroma Reconstruction Method: CACR. . . . . . . . . . . .6
2.1 Chroma-copy Approach to Reconstruct the Missing Chroma Pixels in Flat Regions. . .6
2.2 Non-flat Region-based Winner-first Voting Strategy to Identify the Chroma Subsampling Scheme Used at the Server Side: NRWV. . . . . .7
2.3 Hybrid Approach to Fuse the Missing Chroma Pixels in Non-flat Regions: cs-BLG+BICUBIC. . .9
2.4 Geometry Alignment-based Error Compensation Approach to further Enhance the Quality of the Upsampled Chroma Pixels in Non-flat Regions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3 Experimental Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1 CPSNR and CESIM Quality Merits. . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.2 Visual Effect Merit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17
v3.3 Quality-bitrate Trade-off Merit. . . . . . . . . . . . . . . . . . . . . . . . . 17
4 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
                                

[1] K. L. Chung, C. C. Huang, and T. C. Hsu, “Adaptive Chroma Subsampling-binding and Luma-guided Chroma Reconstruction Method for Screen Content Images” IEEE Transactions on Image Processing, vol. 26, no. 12, pp. 6034-6045, Dec. 2017.
[2] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Section 3.1: Asymptotic notation, Third Ed., The MIT Press, London, England, 2009.
[3] Experimental results, ftp://140.118.175.164/CACR_Exp.
[4] K. He, J. Sun, and X. Tang, “Guided Image Filtering,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, pp. 1397-1409, Jun. 2013.
[5] J. Korhonen, “Improved Image Fidelity by Luma-assisted Chroma Subsampling,” IEEE International Conference on Multimedia and Expo, pp. 1-6, Jul. 2015.
[6] X. Li and M. T. Orchard, “New edge-directed Interpolation,” IEEE Transactions on Image Processing, vol. 10, no. 10, pp. 1521-1527, Oct. 2001.
[7] Z. Ni, L. Ma, H. Zeng, C. Cai, and K. Ma, “Gradient Direction for Screen Content Image Quality Assessment,” IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1394-1398, Oct. 2016.
[8] Z. Ni, L. Ma, H. Zeng, J. Chen, C. Cai, and K. Ma, “ESIM: Edge Similarity for Screen Content Image Quality Assessment,” IEEE Trans. Image Process, vol. 26, no. 10, pp. 4818-4831, Jun. 2017.
[9] W. Pu, M. Karczewicz, R. Joshi, V. Seregin, F. Zou, J. Sole, Y. C. Sun, T. D. Chuang, P. Lai, S. Liu, S. T. Hsiang, J. Ye, and Y. W. Huang, “Palette Mode Coding in HEVC Screen Content Coding Extension,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 6, no. 4, pp. 420-432, Dec. 2016.
[10] T. Vermeir, J. Slowack, R. Van Belle, S. Van Leuven, G. Van Wallendael, J. De Cock, and R. Van de Walle, “Guided Chroma Reconstruction for Screen Content Coding,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 10, pp. 1884-1892, Oct. 2016.
[11] S. Wang, K. Gu, S. Ma, and W. Gao, “Joint Chroma Downsampling and Upsampling for Screen Content Image,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 9, pp. 1595-1609, Sep. 2016.
[12] H. Yu, R. Cohen, K. Rapaka, and J. Xu, Common Test Conditions for Screen Content Coding, document JCTVC-X1015, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11 24th Meeting, Geneva, CH, May/Jun. 2016.
[13] X. Zhang, “Image Interpolation by Adaptive 2-D Autoregressive Modeling and Soft-decision Estimation,” IEEE Transactions on Image Processing, vol. 17, no. 6, pp. 887-896, Jun. 2008.
[14] Y. Zhang, D. Zhao, J. Zhang, R. Xiong, and W. Gao, “Interpolation-dependent Image Downsampling,” IEEE Transactions on Image Processing, vol. 20, no. 11, pp. 3291-3296, Nov. 2011.

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