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研究生: 王盛弘
Sheng Hong Wang
論文名稱: 彩色影像處理流程設計
The Design of Color Image Processing Pipeline
指導教授: 黃奇武
Huang, Chi-Wu
高文忠
Kao, Wen-Chung
學位類別: 碩士
Master
系所名稱: 機電工程學系
Department of Mechatronic Engineering
論文出版年: 2006
畢業學年度: 94
語文別: 中文
論文頁數: 100
中文關鍵詞: 彩色影像處理流程自動色階自動白平衡色彩校正色彩空間轉換色彩飽和度增強伽瑪校正色溫曲線色彩矩陣查表法動態範圍標準色卡點陣圖
英文關鍵詞: Color Image Processing Pipeline, Auto Level, Auto White Balance, Color Correction, Color Space Transformation, Color Saturation Enhancement, Gamma Correction, Color Temperature Curve, Color Matrix, Look Up Table, Dynamic Range, Standard Color Checker, Bitmap
論文種類: 學術論文
相關次數: 點閱:397下載:163
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  • 本篇論文提出一個彩色影像處理流程,將CCD或CMOS感測器上擷取到的原始資料處理為正確顏色的照片。儘管有許多個別的彩色影像處理方法已經被發表,但卻沒有優良的彩色影像處理流程被提出。在此,我們不但提出一個彩色影像處理流程,以及色彩及色階重現演算法。它為彩色影像處理系統中的理論影像科學和實際影像處理流程之間的缺口建立起橋樑。而經由實驗的結果可得知,提出的影像處理流程和新的色彩處理演算法在大部份的場景以及光源下,都可以得到不錯的結果。

    This thesis presents a new color image processing pipeline (IPP) which processes the image raw data captured from CCD/CMOS sensors to the final color and tone corrected picture. Although many individual image processing steps have been well addressed, very few good image pipeline designs proposed to integrate these processing stages. In this thesis, we present a new IPP as well as several color and tone reproduction algorithms. It bridges the gap between theoretic color imaging sciences and the practical IPP implementation issues of digital imaging systems. The demonstrations by processing different scenes of pictures show that the proposed pipeline and several new color processing algorithms runs well in diversified scenes and illuminants.

    第 一 章 論文介紹...........................................1 1.1 研究動機................................................1 1.2 相關研究................................................2 1.2.1 彩色影像處理流程......................................2 1.2.2 自動白平衡............................................4 1.2.3 色彩校正..............................................7 1.2.4 色彩空間轉換..........................................7 1.3 問題探討................................................8 1.4 提出方法................................................9 1.5 論文架構...............................................12 第 二 章 系統架構..........................................13 第 三 章 彩色影像處理流程學理與相關研究....................16 3.1 自動色階...............................................16 3.2 自動白平衡.............................................16 3.3 色彩校正...............................................19 3.4 色彩空間轉換...........................................20 3.5 色彩飽和度增強.........................................20 3.6 伽瑪校正...............................................21 第 四 章 彩色影像處理軟體演算法............................22 4.1 自動色階演算法.........................................22 4.2 自動白平衡演算法.......................................23 4.3 自動白平衡誤差量測.....................................27 4.4 色彩校正演算法.........................................27 4.5 色彩空間轉換演算法.....................................28 4.6 色彩飽和度增強演算法...................................30 4.7 伽瑪校正演算法.........................................31 第 五 章 嵌入式軟體系統設計................................33 5.1 數位信號處理器發展平台簡介.............................33 5.2 執行構想...............................................34 5.3 發展平台環境介紹.......................................34 5.4 查表法介紹.............................................37 5.5 DSP演算法實作..........................................38 5.5.1 自動色階DSP實作......................................39 5.5.2 自動白平衡DSP實作....................................39 5.5.3 色彩校正DSP實作......................................42 5.5.4 色彩空間轉換DSP實作..................................42 5.5.5 色彩飽和度增強DSP實作................................45 5.5.6 伽瑪校正DSP實作......................................46 5.6 問題討論...............................................47 第 六 章 實驗結果..........................................49 6.1 彩色影像處理系統的輸入與輸出...........................49 6.2 彩色影像處理流程模擬...................................52 6.3 彩色影像處理流程影像效果...............................54 6.3.1 自動色階影像效果.....................................58 6.3.2 自動白平衡影像效果...................................59 6.3.3 色彩校正影像效果.....................................60 6.3.4 色彩飽和度增強影像效果...............................61 6.3.5 伽瑪校正影像效果.....................................62 6.3.6 自動白平衡效能評估...................................63 6.4 嵌入式軟體系統效能評估.................................67 6.5 嵌入式軟體系統效能比較.................................67 6.6 嵌入式軟體系統效果呈現.................................68 6.6.1 陰天影像.............................................70 6.6.2 上午影像.............................................71 6.6.3 下午影像.............................................72 6.6.4 室內影像.............................................73 6.6.5 缺少自動色階處理.....................................74 6.6.6 缺少自動白平衡處理...................................75 6.6.7 缺少色彩校正處理.....................................75 6.6.8 缺少色彩飽和度增強處理...............................76 6.6.9 缺少色調重現處理.....................................77 第 七 章 結論與未來展望....................................79 7.1 色彩學................................................79 7.2 嵌入式系統.............................................79 7.3 數位信號處理器.........................................80 參考文獻...................................................81 附錄一 參考資料............................................83 附錄二 工作環境............................................85 索引......................................................86 基本簡歷...................................................87 論文發表...................................................88

    [1] G. Sharma and H. J. Trussell, “Digital color imaging,” IEEE Trans. Image Processing, vol. 6, no, 7, pp. 901-932, Jul. 1997.
    [2] G. Sharma, M. J. Vrhel, and H. J. Trussell, “Color imaging for multimedia,” Proceedings of the IEEE, vol. 86,no. 6, pp. 1088-1108, Jun. 1998.
    [3] H. C Lee, Introduction to Color Imaging Science, Cambridge University Press, pp. 46-47, pp.388-392 and pp. 450-459, 2005.
    [4] K. Illgner, H-G Gruber, P. Gelabert, J. Liang,, Y. Yoo, W. Rabadi, R. Talluri, "Programmable DSP platform for digital still cameras", in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Mar. 1999, pp. 2235-2238.
    [5] C. C. Koh, Student Member, IEEE, J. Mukherjee, Member, IEEE, and S.K. Mitra, Life Fellow, IEEE, ”New Efficient Methods of Image Compression in Digital Cameras with Color Filter Array”, IEEE Trans. Consumer Electronics, vol. 49, NO. 4, pp 1448-1456, Sept. 4, 2003.
    [6] H. Quinn, S. King, M. Leeser, W. Meleis, ”Runtime Assignment of Reconfigurable Hardware Components for Image Processing Pipelines”, Proceedings of the 11th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM’03), 2003.
    [7] F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recognition, vol. 37, no. 6, pp. 1201-1217, 2004.
    [8] K. Barnard, V. Cardei, and B. Funt, “A comparison of computational color constancy algorithms-part I: methodology and experiments with synthesized data,” IEEE Trans. Image Processing, vol. 11, no. 9, pp. 972-983, Sep. 2002.
    [9] K. Barnard, V. Cardei, and B. Funt, “A comparison of computational color constancy algorithms-part II: experiments with image data,” IEEE Trans. Image Processing, vol. 11, no. 9, pp. 985-996, Sep. 2002.
    [10] B. Funt, K. Barnard, and L. Martin, “Is machine colour constancy good enough?” Proc. 5th European Conference Computer Vision, Freiburg, Germany, pp. 445-459, 1998.
    [11] B. Funt, V.Cardei, and K. Barnard, “Learning color constancy,” Proceedings of the Fourth IS&T/SID Color Imaging Conference, pp. 58-63, 1996.
    [12] G. D. Finlayson, S. D. Hordley, and P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 11, pp. 1209-1221, Nov. 2001.
    [13] G.D. Finlayson and S.D. Hordley, “Color constancy at a pixel,” Journal of the Opt. Soc. Am. A, vol. 18, no. 2, pp. 253-264, 2001.
    [14] Edmund Y. Lam, “Combining Gray World and Retinex Theory for Automatic White Balance in Digital Photography,” IEEE, pp. 134-139, 2005.
    [15] Ching-Chih Weng, Homer Chen, and Chiou-Shann Fuh, “A Novel Automatic White Balance Method For Digital Still Cameras,” Proc. IEEE ISCAS Int. Symposium on Circuits and Systems, pp. 3801-3804, 2005.
    [16] Hany Farid. “Blind Inverse Gamma Correction,” IEEE Trans. Image Processing. 8. 2001.
    [17] F. H. Cheng, W. - H. Hsu, and T. W. Chen, “Recovering colors in an image with chromatic illuminant,” IEEE Trans. Image Processing, vol. 7, no. 11, pp.1524-1533, Nov. 1998.
    [18] Y. C. Chang and J. F. Reid, “RGB calibration for color image analysis in machine vision,” IEEE Trans. Image Processing, vol. 5, no. 10, pp. 1414-1422, Oct. 1996.
    [19] M. Jackowski, A. Goshtasby, S. Bines, D. Roseman, and C. Yu, “Correcting the geometry and color of digital images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 10, pp. 1152- 1158, Oct. 1997.
    [20] M. J. Vrhel and H. J. Trussell, “Color device calibration: a mathematical formulation,” IEEE Trans. Image Processing, vol. 8, no. 12, pp. 1796-1806, Dec. 1999.
    [21] E. Mizutani and K. Nishio, “Multi-illuminant color reproduction for electronic cameras via CANFIS neuro-fuzzy modular network device characterization,” IEEE Trans. Neural Network, vol. 13, no. 4, pp. 1009-1022, Jul. 2002.
    [22] C. Connolly and T. Fliess, “A study of efficiency and accuracy in the transformation from RGB to CIELab color space,” IEEE Trans. Image Processing, vol. 6, pp.1046–1048, July 1997.
    [23] H. C. Lee, "Digital Color Image Processing Method Employing Constrained Correction of Color Reproduction Function", U.S. Patent, 4,663,663, May 5, 1987.
    [24] C. S. Mccamy, H. Marcus, and J. G. Davidson, “A color-rendition chart.” J. Applied Photographic Eng., vol. 2,no. 3, pp. 95-99, 1976.

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