簡易檢索 / 詳目顯示

回結果列表
研究生： 黃志源
Chih-Yuan Huang
論文名稱： 提高彩度抽樣品質之基於雙三次卷積插值法的迭代亮度優化方法
An Effective Bicubic Convolution Interpolation-Based Iterative Luma Optimization for Enhancing Quality in Chroma Subsampling
指導教授： 鍾國亮
Kuo-Liang Chung
口試委員: 鍾國亮
Kuo-Liang Chung
貝蘇章
Soo-Chang Pei
范國清
Kuo-Chin Fan
廖弘源
Hong-Yuan Liao
鮑興國
Hsing-Kuo Pao
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： 2022
畢業學年度： 110
語文別： 英文
論文頁數： 49
中文關鍵詞： 色度下採樣優先之亮度修改 (CSFLM) 、凸性失貞函數 、迭代亮度優化 、品質位元率權衡 、品質提升 、RGB全彩圖像 、多功能視頻編碼 (VVC)
外文關鍵詞： Chroma subsampling-first luma modification (CSFLM), convex distortion function, iterative luma optimization, quality-bitrate tradeoff, quality enhancement, RGB full-color image, versatile video coding (VVC)
相關次數： 點閱：197  下載：2 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  •  上一筆

    • 傳統上，在壓縮 RGB 全彩圖像之前，對於每個轉換成的 2$\times$2 CbCr 區塊 $B^{CbCr}$，色度下採樣僅對 $B^{CbCr}$ 進行下採樣，但不會更改亮度塊 $B^{Y}$。在目前的研究中，一種特殊的基於線性插值，即基於COPY的色度二次採樣優先亮度修改（CSFLM）研究試圖改變亮度塊以提高重建RGB全彩圖像的質量。在本文中，提出了一種快速有效的非線性插值，即雙三次卷積插值（BCI），基於CSFLM的迭代亮度修改方法。在我們的迭代方法中，首先提供了一個基於 BCI 的失真函數及其凸屬性證明。接下來，在提出的凸性失真函數的基礎上，應用偽逆技術獲得初始亮度修正解，然後提出了一種迭代方法來改進初始亮度修正解。基於IMAX、柯達、SCI（屏幕內容圖像）、CI（經典圖像）和視頻數據集五個測試圖像數據集，徹底的實驗結果表明，在新發布的多功能視頻編碼（VVC）平台VTM-12.0 中，與現有的最先進方法相比，我們的迭代亮度修改方法實現了顯著的質量、執行時間和質量比特率權衡改進。

    Traditionally, prior to compressing an RGB full-color image, for each converted 2$\times$2 CbCr block $B^{CbCr}$, chroma subsampling only downsamples $B^{CbCr}$, but without changing the luma block $B^{Y}$ at all. In the current research, a special linear interpolation-based, namely the COPY-based, chroma subsampling-first luma modification (CSFLM) study has attempted to change the luma block for enhancing the quality of the reconstructed RGB full-color image. In this thesis, a fast and effective nonlinear interpolation, namely the bicubic convolution interpolation (BCI), based iterative luma modification method for CSFLM is proposed. In our iterative method, a BCI-based distortion function and its convex property proof are first provided. Next, based on the proposed convex distortion function, a pseudoinverse technique is applied to obtain the initial luma modification solution, and then an iterative method is proposed to improve the initial luma modification solution. Based on five testing image datasets, namely the IMAX, Kodak, SCI (screen content images), CI (classical images), and Video datasets, the thorough experimental results have demonstrated that on the newly released Versatile Video Coding (VVC) platform VTM-12.0, our iterative luma modification method achieves substantial quality, execution-time, and quality-bitrate tradeoff improvements when compared with the existing state-of-the-art methods.

    指導教授推薦書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 論文口試委員審定書 . . . . . . . . . . . . . . . . . . . . . . . . . ii Abstract in Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . iii Abstract in English . . . . . . . . . . . . . . . . . . . . . . . . . . iv Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x List of Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . xi 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Related Chroma Subsampling Works . . . . . . . . . . . . 2 1.2 Related CSFLM Works . . . . . . . . . . . . . . . . . . . 2 1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3.1 The first contribution . . . . . . . . . . . . . . . . 6 1.3.2 The second contribution . . . . . . . . . . . . . . 6 1.3.3 The third contribution . . . . . . . . . . . . . . . 7 2 The Proposed New Bci-based Pixel-distortion Function . . . . . 8 v 2.1 The Proposed Pixel-Distortion Function . . . . . . . . . . 8 2.1.1 The estimation of (Cbest i , Crest i ) . . . . . . . . . . 8 2.1.2 The proposed pixel-distortion function . . . . . . . 11 2.2 Convex Property Proof of the Proposed Pixel-Distortion Function . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3 The Proposed Fast And Effective Iterative Luma Modification Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.1 Determining the Initial Integer Luma Modification Solution 16 3.2 The Proposed Iterative Luma Modification Method . . . . 19 4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . 23 4.1 Quality and Execution Time Improvements of Our Luma Modification Method . . . . . . . . . . . . . . . . . . . . 24 4.1.1 Quality enhancement merit . . . . . . . . . . . . . 25 4.1.2 Execution time merit . . . . . . . . . . . . . . . . 26 4.2 Visual Effect and BD-rate Merits of Our Luma Modifica- tion Method . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.2.1 The visual effect merit . . . . . . . . . . . . . . . 26 4.2.2 The BD-rate merit . . . . . . . . . . . . . . . . . 28 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

    [1] G. Bjøntegaard, Calculation of average PSNR difference between RD-curves, ITU-T SG16/Q6 VCEG, Austin, TX, USA, document VECGM33, pp. 2-4, Apr. 2001.
    [2] S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge, U.K.: Cambridge Univ. 2004, pp. 67.
    [3] G. Bradski and A. Kaehler, Learning OpenCV: Comput. Vision with the OpenCV Library. Sebastopol, CA, USA: O’Reilly Media, 2008.
    [4] K. L. Chung, T. C. Hsu, and C. C. Huang, “Joint chroma subsampling and distortion-minimization-based luma modification for RGB color images with application,”IEEE Transactions on Image Processing, vol. 26, no. 10, pp. 4626-4638, Oct. 2017.
    [5] Execution code of the our BCI-based iterative luma modifi-cation method. [Online]. Available: Ftp://140.118.175.164/CSFLM/CSFLM.zip.
    [6] HM-16.18. Accessed on Jan. 2018. [Online]. Available: https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/tags/HM-16.18/
    [7] IMAX True Color Image Collection. Accessed: Aug. 2014. [Online]. Available:https://www4.comp.polyu.edu.hk/~cslzhang/CDM_Dataset.htm
    [8] Studio encoding parameters of digital television for standard 4:3 and wide-screen 16:9 aspect ratios, document Rec. ITU-R BT-601-5, ITU, 2011.
    [9] R. G. Keys, “Cubic convolution interpolation for digital image processing,” IEEE transactions on acoustics, speech, and signal processing, vol. 29, no. 6, pp. 1153-1160, Jan. 28, Dec. 1981.
    [10] Kodak True Color Image Collection. Accessed: Aug. 2014. [Online]. Available: https://www.math.purdue.edu/~lucier/PHOTO_CD/BMP_IMAGES/
    [11] T. L. Lin, B. H. Liu, and K. H. Jiang, “An efficient algorithm for luminance optimization in chroma downsampling,”IEEE Transactions on Circuits and Systems for Video Technology, Early Access, 2021.
    [12] A. Luthra, E. François, and W. Husak, Call for evidence (CfE) for HDR and WCG video coding, Standard ISO/IEC JTC1/SC29/WG11 (MPEG), Geneva, Switzerland, Feb. 2015.
    [13] Open CV codes. Accessed: Nov. 2018. [Online]. Available: https://sourceforge.net/projects/opencvlibrary/?fbclid=IwAR2vXid_ZecTmGKWiCuOe2XuaCKdAq4-Aes7FfeEVIpDM-BwOJAgg6TbI-k
    [14] SCI Image Database. Accessed: Jan. 10, 2016. [Online]. Available: ftp://140.118.175.164/SCI
    [15] Spatial Scalability Filters, document ISO/IEC JTC1/SC29/WG11 ITU-T SG 16 Q.6, Jul. 2005.
    [16] M. Tachi, “Image processing device, image processing method, and program pertaining to image correction,”U.S. Patent 8,314,863, Nov. 20, 2012.
    [17] The Video Dataset. Accessed: Apr. 2020. [Online]. Available: ftp: //140.118.175.164/CFASS/
    [18] VTM-11.0. Accessed: 2021. [Online]. Available: https://vcgit.hhi.fraunhofer.de/jvet//VVCSoftware_VTM
    [19] Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,”IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, Apr. 2004.
    [20] S. Zhu, C. Cui, R. Xiong, Y. Guo, and B. Zeng, “Efficient chroma subsampling and luma modification for color image compression,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 5, pp. 1559-1563, May. 2019.
    [21] S. Zhu, M. Li, C. Chen, S. Liu, and B. Zeng, “Cross-space distortion directed color image compression,” IEEE Transactions on Multimedia, vol. 20, no. 3, pp. 525-538, 2018, Mar. 2018.

    QR CODE