高速攝影機在工業界、學術界及體育界等領域皆有著廣泛的應用，但長久以來，價格昂貴一直是高速攝影機最大的缺點，所幸美國史丹佛大學的計算機圖形實驗室開發出了「史丹佛相機陣列」的架構，並且在高速攝影的應用上有著不錯的成果，然而該架構奢侈且龐大的硬體需求卻可能成為阻礙其發展的因素，因此我們決定將嵌入式系統的開發模式導入該架構中，進而讓基於史丹佛相機陣列的高速攝影系統得以用更便宜及更易於攜帶的平台來實現。
在論文[7]中，我們已經成功的以SoPC平台開發出史丹佛相機陣列的硬體架構，而在本論文中，我們將致力於此平台架構下的軟體系統開發，以及各種影像校正演算法的設計。其中，為了充分發揮硬體平台中的繪圖效能，我們選擇自行開發一套精簡但功能齊全的GUI系統，並利用此系統建構出上層的系統控制介面，以提供使用者進行錄影及影像校正等操作。至於影像校正的部分主要包括了自動曝光及位移誤差校正演算法的設計，而在本論文所提出的演算法中，除了要求準確的校正結果外，執行速度也會是另一個主要的考量。

High speed video camera is used for widespread applications in industry, academia, sporting world and so forth. But the price is the most significant disadvantage all the time. Fortunately, the Stanford Computer Graphic Laboratory develops a “Stanford Multiple Camera Array” architecture and provides a good result in the high-speed videography application. However, the scale of the hardware architecture in their design is too large to be implemented as a portable device. Therefore, we decided to realize the system by reducing the architecture with an embedded platform.
We have redesigned the hardware architecture of the camera array with a SoPC- based platform in [7]. In this paper, we dedicated to design a GUI controlling system and image rectification algorithms for high-speed videography on the SoPC platform. The proposed algorithms are for the most part of auto-exposure and displacement error rectification, and they are designed not only for the accurate rectifying result, the speed will be another key consideration for rectification in this paper.

[1] Standford Computer Graphics Laboratory, “The Stanford Multiple Camera Array”, http://graphics.stanford.edu/projects/array/
[2] Wikipedia, “Eadweard Muybridge”, http://en.wikipedia.org/wiki/Eadweard_Muybridge
[3] 施尚融（2006），高速攝影系統介紹與應用，車輛測試資訊，50 期，2-9頁
[4] Vision Research, “SR-CMOS Technology”, http://www.visionresearch.com/inde x.cfm?sector=htm/files&page=camera_51_new
[5] “Shutter Operations for CCD and CMOS Image Sensors”, Kodak Image Sensor solutions, Application note
[6] NIOS2 Community Wiki, http://nioswiki.jot.com/WikiHome
[7] 鄭子凡，“以多組CMOS感測器實現高速攝影系統之SOPC硬體架構”，國立台灣科技大學電子工程系碩士論文，民國九十六年
[8] De Nayer Instituut, “Auto Exposure”, http://emsys.denayer.wenk.be/emcam/autoexposure.pdf
[9] N. Ahmed, T. Natarajan, and K. R. Rao, "Discrete Cosine Transform", IEEE Trans. Computers, 90-93, Jan 1974
[10] 陳同孝，張真誠，黃國峰，“數位影像處理技術”, 旗標出版
[11] T. Koga, K. Iinurna, A. Hirano, Y. Iijima, and T. Ishiguro, “Motion-compensated interframe coding for video conferencing”, in Proc. NTC 81, pp. C9.6.1-9.6.5, New Orleans, LA, Nov./Dec. 1981.
[12] J.R. Jain and A.K. Jain, “Displacement measurement and its application in interframe image coding”, IEEE Trans. On Communications, vol. COM-29, pp. 1799-808, Dec’81
[13] L. M. Po, and W. C. Ma (1996，1) “A Novel Four-Step Search Algorithm for Fast Block Motion Estimation”, IEEE Tran. on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 313-317.
[14] J. Y. Tham, S. Ranganath, M. Ranganath, and A. A. Kassim, “A novel unrestricted center-biased diamond search algorithm for block motion estimation”, IEEE Trans, Circuits Syst. Video Technol., Vol. 8, No. 4, pp. 369-377, Aug 1998.
[15] B. Wilburn, N. Joshi, V. Vaish, M. Levoy, M. Horowitz, “High-Speed Videography Using a Dense Camera Array”, CVPR, Vol. 2, pp. 294-301, July 2004.
[16] Making movies from image files using ffmpeg/mencoder, http://electron.mit.edu/~gsteele/ffmpeg/
[17] H. Longuet-Higgins, “A computer algorithm for reconstructing a scene from two projections”, Nature, Vol. 293, no. 10, pp.133-135, 1981.
[18] Papadimitriou, D.V. and Dennis, T.J., “Epipolar line estimation and rectification for stereo image pairs”, IEEE Transactions On Image Process, 5(4), pp. 672-676, April 1996.
[19] Hartley, R. and Zisserman,.A., “Multiple View Geometry in Computer Vision”, Cambridge University Press, 2004.
[20] Pollefeys M, Koch R, van Gool L. “A simple and efficient rectification method for general motion.” In Werner B, ed. Proc. of the Int'l Conf. on Computer Vision. Los Alamitos: IEEE Press, 1999. 496~501.