簡易檢索 / 詳目顯示

回結果列表
研究生： 黃紹綱
Huang, Shao-Kang
論文名稱： 基於自我運動速度估測分析之數位影像穩定器
Digital Image Stabilizer Based on Ego-motion Velocity Analysis
指導教授： 高文忠
Kao, Wen-Chung
學位類別： 碩士
Master
系所名稱： 電機工程學系
Department of Electrical Engineering
論文出版年： 2013
畢業學年度： 101
語文別： 中文
論文頁數： 86
中文關鍵詞： 數位影像穩定器 、自我運動向量估計演算法
英文關鍵詞： digital image stabilizer, ego-motion estimation
論文種類： 學術論文
相關次數： 點閱：336  下載：11 
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

    • 數位影像穩定器，主要為了移除影片中非預期的運動向量，是應用在手持相機錄影或行車紀錄器上一個理想相機必須擁有的功能。優秀的數位影像穩定器應能濾除抖動運動向量，但仍能保留所欲的運動向量。

    在本文中，我們基於多個幀之間運動向量算得的速度來進行分析，並提出一個新的數位影像穩定器。透過更準確的自我運動向量估計演算法，我們處理的影片成果能比其他已提出方法有更加的視覺品質。

    The digital image stabilization (DIS), which removes unwanted motions, is a desirable camera capability for taking videos with a hand-held camera or a recorder installed on moving vehicles. A good DIS should be able to remove jitter motions but still remains the intentional ego-motion. In this thesis, we present a new DIS based on motion velocity analysis among several successive frames. By relying on a more accurate ego-motion estimation algorithm, the processed video shows better visual quality than other published works.

    中文摘要 .................................................ii 英文摘要 .................................................iii 誌　　謝 .................................................iv 目　　錄 .................................................v 圖目錄 .................................................vii 表目錄 .................................................ix 第一章 緒論...............................................1 1.1 研究動機及背景.......................................1 1.2 相關問題概述.........................................5 1.3 本文研究方法.........................................8 第二章 相關研究探討.........................................9 2.1 影像穩定器系統基本架構與流程............................9 2.2 區域運動向量估計研究.................................10 2.3 全域運動向量估計研究.................................15 2.4 補償值估計演算法探討.................................17 2.5 影像補償之簡介......................................22 第三章 數位影像穩定器演算法系統架構...........................24 3.1 系統流程方塊圖......................................24 3.2 背景區域之篩選......................................25 3.3 權重式移動平均系統簡介................................26 第四章 系統各模組演算法探討.................................28 4.1 區域運動向量估計....................................28 4.2 全域運動向量估計....................................31 4.3 運動向量補償值估計...................................36 第五章 研究結果...........................................55 5.1 實驗環境及說明......................................55 5.2 影像穩定成果比較....................................56 第六章 結論與未來展望......................................75 6.1 結論..............................................75 6.2 未來展望...........................................76 參考文獻...................................................77 附 錄 ...................................................80

    [1] K. Sato, S. Ishizuka, A. Nikami, and M. Sato, “Control techniques for optical image stabilizing system,” IEEE Trans. Consum. Electron., vol. 39, no. 3, pp. 461-466, Aug. 1993.
    [2] Canon, “What is vari-angle prism image stabilizer (VAP-IS).” Available online: http://www.canon.com/bctv/faq/vari.html.
    [3] Canon, “What is optical shift image stabilizer.” Available online: http://www.canon.com/bctv/faq/optis.html.
    [4] Canon, “Optical image stabilizer.” Available online: http://www.usa.canon.com/cusa/consumer/standard_display/Lens_Advantage_IS.
    [5] Nikon, “Vibration reduction (VR) technology.” Available online: http://imaging.nikon.com/history/scenes/16/.
    [6] Panasonic, “Panasonic Mega O.I.S.” Available online: https://panasonic.ca/english/audiovideo/camerascamcorders/digitalstill/megaOIS.asp.
    [7] H. J. Chang, P. J. Kim, D. S. Song, J. Y. Choi, “Optical image stabilizing system using multirate fuzzy PID controller for mobile device camera,” IEEE Trans. Consum. Electron., vol. 55, no. 2, pp. 303-311, May 2009.
    [8] H. R. Pourreza, M. Rahmati, F. Behazin, “An electronic digital image stabilizer based on stationary wavelet transform (SWT),” in Proc. 2003 Int. Conf. on Image Process., vol. 2, Sep. 2003, pp. II-383-386.
    [9] S. Ertürk, “Image sequence stabilisation: motion vector integration (MVI) versus frame position smoothing (FPS),” in Proc. 2nd Int. Symp. on ISPA, 2001, pp. 266-271.
    [10] K. Ioannidis and I. T. Andreadis, “A digital image stabilization method based on the Hilbert–Huang transform,” IEEE Trans. Instrum. Meas., vol. 61, no. 9, pp. 2446-2457, Sep. 2012.
    [11] S. C. Hsu, S. F. Liang, K. W. Fan, and C. T. Lin, “A robust in-car digital image stabilization technique,” IEEE Trans. Syst. Man Cybern., vol. 37, no. 2, pp. 234-247, Mar. 2007.
    [12] Y. G. Ryu and M. J. Chung, “Robust online digital image stabilization based on point-feature trajectory without accumulative global motion estimation,” IEEE Signal Process. Lett., vol. 19, no. 4, pp. 223-226, 2012.
    [13] C. Wang, J. H. Kim, K. Y. Byun, J. Ni, and S. J. Ko, “Robust digital image stabilization using the Kalman filter,” IEEE Trans. Consum. Electron., vol. 55, no. 1, pp. 6-14, 2009.
    [14] A. A. Amanatiadis and I. Andreadis, “Digital image stabilization by independent component analysis,” IEEE Trans. Instrum. Meas., vol. 59, no. 7, July 2010.
    [15] C. T. Lin, C. T. Hong, and C. T. Yang, “Real-time digital image stabilization system using modified proportional integrated controller,” IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 3, pp. 427-431, Mar. 2009.
    [16] Y. Matsushita, E. Ofek, W. Ge, X. Tang, and H.Y. Shum, “Full-frame video stabilization with motion inpainting,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 7, pp. 1150 – 1163, July 2006.
    [17] S. J. Ko, S. H. Lee, and K. H. Lee, “Digital image stabilizing algorithms based on bit-plane matching,” IEEE Trans. Consum. Electron., vol. 44, no. 3, pp. 617-622, Aug. 1998.
    [18] S. J. Ko, S. H. Lee, S. W. Jeon, and E. S. Kang, “Fast digital image stabilizer based on gray-coded bit-plane matching,” IEEE Trans. Consum. Electron., vol. 45, no. 3, pp. 598-603, Aug. 1999.
    [19] Q. Zeng, H. Wang, and X. Ma, “On-line digital image stabilization for translational and rotational motion,” Int. Conf. on IASP, 21-23 Oct. 2011, pp. 266-270.
    [20] C. H. Cheung and L. M. Po, “A novel cross-diamond search algorithm for fast block motion estimation,” IEEE Trans. Circuits Syst. Video Technol., vol. 12, no. 12, pp. 1168-1177, Dec. 2002.
    [21] L. Xu and X. Lin, “Digital image stabilization based on circular block matching,” IEEE Trans. Consum. Electorn., vol. 52, no. 2, pp. 566-574, May 2006.
    [22] J. Shi, C. Tomasi, “Good Features to Track,” in IEEE Conf. on Computer Vision and Pattern Recognition, 1994, pp. 593-600.
    [23] G. Welch and G. Bishop, “An introduction to the Kalman filter,” in SIGGARPH2001 Course Note, 2001 : Univ. North Carolina.
    [24] M. Bertalmio, G. Sapiro, V. Casellas, and C. Ballester, “Image inpainting,” in Proc. of the Int. Conf. on Computer Garaphics and Interactive Techniques, New Orleans, LA, USA, July 2000, pp.417-424.
    [25] Y. Wexler, E. Shechtman, and M. Irani, “Space-time video completion,” in Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, Washington, D.C., USA, June/July 2004, vol. 1, pp. 120-127.
    [26] S. C. Hse, S.F. Liang, and C. T. Lin, “A robust digital image stabilization technique based on inverse triangle method and background detection,” IEEE Trans. Consum. Electron., vol. 51, no. 2, pp. 335–345, May 2005.
    [27] W. C. Kao, S. H. Chen, P. Y. Hsiao, “Real-time image stabilization for digital video cameras,” in Proc. of the IEEE Asia Pacific Conf. on Circuits and Systems, Singapore, Dec. 2006, pp. 1651-1654.
    [28] Rastislav Lukac, Single-sensor imageing methods and applications for digital cameras, CRC Press Taylor & Francis Group, Boca Raton 2009.

    下載圖示
    QR CODE