簡易檢索 / 詳目顯示

回結果列表
研究生： 鄒逸凡
Yi-Fan Chou
論文名稱： 利用數位相機進行光譜重建
Obtaining Reflectance Functions Using Digital Cameras
指導教授： 羅明
Ronnier M Luo
李三良
San-Liang Lee
口試委員: 歐陽盟
Ou-Yang Mang
羅梅君
Mei-chun Lo
孫沛立
Pei-Li Sun
溫照華
Chao-hua Wen
學位類別： 博士
Doctor
系所名稱： 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年： 2012
畢業學年度： 101
語文別： 英文
論文頁數： 221
中文關鍵詞： 色彩量測 、分光光度計 、相機校正 、光譜估測
外文關鍵詞： colour measurement, spectrophotometer, camera characterisation, reflectance estimation
相關次數： 點閱：328  下載：12 
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

    • 　　物體顏色可用其光譜反射率準確表示，此研究首先探討並比較多種量測反射率之方法。傳統上，利用分光光度計測色，但此種儀器設備為接觸式量測，一次只能量測單一色塊，且測試樣品表面須為均勻平面。而利用數位相機測色則可以克服這個限制，但系統準確性及精確性則會低於分光光度計。本論文將討論測色方法及顏色預估方法，前者包含分光光度計的測色效能，後者包含數位相機色彩特性校正模型，透過此特性校正模型可將數位相機數位訊號轉換成物體光譜反射率。
    　　此研究主要致力於數位相機的色彩演算技術開發，一般常用在相機的特性校正模型是將相機數位訊號的設備從屬色彩訊號RGB轉成非設備從屬色彩訊號，如XYZ或CIELAB色彩空間。此種特性校正模型需要一組目標特性校正色卡用來當作訓練資料，而要成功建立此模型取決於如何有效選擇這些顏色。因此在本論文中，提出一個新的方法去選取目標特性校正色塊，並指出那些顏色區域是重要的，特性校正色卡必須包含這些區域。
    　　以上這種基於非設備從屬色彩空間XYZ的特性校正模型，隨著光源改變會有不同模型，XYZ值也會跟著不同光源而有所改變。較好的方法去記錄色彩資訊，是直接將相機數位每個像素的訊號轉成光譜反射率值。五種常用的反射率還原演算法包含平滑限制、基函數、基函數平滑限制、溫納估計及假反置演算法。在此論文中，會用這五種方法將XYZ值還原至光譜反射率，另外有兩種自適應演算法將用來改善這五種基本演算法，此自適應演算法包含區域化訓練資料及權重矩陣。這些演算法的效能將用十萬個光譜數據來做測試，另外從這十萬個光譜數據中發展出一組基函數，可以成功的用線性方程式表示所有光譜數據。
    　　此論文發現，溫納估計或假反置演算法同時加上區域化訓練資料及權重矩陣可以有最好的效果。同樣的方法套用在數位相機RGB訊號值上，光譜反射率亦可以成功被還原，假反制演算法加上兩種自適應演算法可以最準確的還原光譜資料，用CIE2000色差公式來評估此演算法，其精度可小於一個色差值。

    Spectral reflectance is the ‘finger print’ of the colour of an object. This study investigated a number of the methods to obtain spectral reflectance functions of colours, and to compare their performance. Spectrophotometers are traditionally colour measurement instruments. However, they can only measure one spot of flat uniform colour patches with direct contact. Using digital cameras as a means of colour measurement device to predict spectral reflectance can overcome this limitation, but system performance in terms of accuracy and precision is expected to be lower than using spectrophotometers. In the present work, the metrology and prediction of measuring colours were studied. The former included the evaluation of spectrophotometer performance. The latter considered characterisation models using digital cameras to predict spectral reflectance from camera responses.

    Large efforts were spent to develop camera based technology. The characterisation model which was typically applied to transform the camera primary responses to device independent primaries (XYZ or CIELAB) requires a characterisation target. To make a successful model depends upon the selection of effective colours in the characterisation target. In the present research, a method for developing the characterisation target and the importance of colour regions for colour selection were proposed.

    Using the colorimetry (XYZ) based characterisation models is illuminant dependency. A better way for colour specification using a digital camera is to estimate the reflectance of surface colours in a pixel-by-pixel basis. Five widely used methods including smoothness constraint, basis functions, basis functions with smoothness constraint, Wiener estimation and Pseudo-inverse were investigated for the reconstruction of reflectance function from the tristimulus values. Two adaptive methods including the localised set and the weighted matrix were applied to the basic methods. A set of 100,000 spectra was collected to evaluate the performance. A set of basis functions was also derived from the set which can represent all world colours. It was found that the Wiener estimation and pseudo-inverse methods modified by the adaptive methods performed the best among. The same techniques were applied to estimate reflectance functions from camera RGB response. The pseudo-inverse method with a localised set and weighted matrix gave the highest accuracy of 1.0 ΔE00.

    論文摘要 i Abstract ii Acknowledgements iii Table of Contents iv List of Tables ix List of Figures xii List of Abbreviations xvi Chapter 1 Introduction 1 1.1 Background 2 1.2 Aims and Objectives 4 1.3 Thesis Structure 4 1.4 Summary of Contribution of Knowledge 5 1.5 Related Publications 6 1.6 Other Publications 7 Chapter 2 Literature Survey 8 2.1 Colorimetry 9 2.1.1 Visible Spectrum 9 2.1.2 CIE Standard Illuminants 11 2.1.3 Object 14 2.1.4 CIE Colour Matching Function 15 2.1.5 Tristimulus Value Calculation 17 2.1.6 ASTM Weighting Tables 20 2.1.7 Uniform Colour Space 20 2.1.8 Colour Difference Formulae 22 2.1.8.1 CIELUV and CIELAB Formulae 23 2.1.8.2 CIEDE2000 Formula 24 2.1.9 Metamerism 26 2.2 Colour Measuring Instruments 28 2.2.1 Tristimulus Colorimeter 29 2.2.2 Spectrophotometer 30 2.2.3 Reflectance Measurement 31 2.2.4 Spectrophotometer Light Sources 32 2.2.5 Instrument Geometries of Illuminating and Viewing 33 2.2.6 The Dual-Beam Spectrophotometer 35 2.2.7 Instrument Calibration 35 2.2.8 Specifications of Spectrophotometers 36 2.2.8.1 Instrument Specifications 36 2.2.8.2 Performance Specifications 36 2.3 Digital Camera Characterisation 37 2.3.1 Digital Still Camera 37 2.3.2 Device Independent and Dependent Colour Space 39 2.3.3 Digital Camera Characterisation Models 39 2.3.3.1 Polynomial Model 41 2.4 Linear Models for Reflectance Representation 45 2.4.1 Principal Component Analysis (PCA) 45 2.4.2 Metrics for Spectral Match Quality 48 2.4.3 Basis Functions of Munsell Reflectance Spectra 50 2.4.4 Basis Functions of Paint and Artwork Reflectance 53 2.4.5 Basis Functions of Human Skins 55 2.4.6 Basis Functions of Natural Objects 55 2.5 Reflectance Estimation Techniques 60 2.5.1 Moore-Penrose Pseudo-Inverse 61 2.5.2 Smoothness Constraint 62 2.5.3 Basis Function 64 2.5.4 Basis Function with Smoothness Constraint 65 2.5.5 Wiener Estimation Method 66 2.5.6 Adaptive Methods Based on Training Set Selection 66 2.5.6.1 Shen et al.’s Adaptive Wiener Estimation 67 2.5.6.2 Babaei et al.’s Weighted Matrix 68 2.6 Summary 69 Chapter 3 Experimental Preparation 71 3.1 Instruments 72 3.1.1 The Spectrophotometers Used in This Study 72 3.1.1.1 GretagMacbethTM COLOR-EYE® 7000A Spectrophotometer (CE7000A) 72 3.1.1.2 Datacolor Spectraflash 600 (SF600) 73 3.1.1.3 X-RiteTM Color ITM7 73 3.1.1.4 X-RiteTM 962 74 3.1.1.5 SpectroEye 74 3.1.1.6 Overview 74 3.1.2 Camera Measurement System 76 3.1.2.1 Collection of Raw Camera Response with Linearization and Spatial Correction 77 3.2 Sample Sets 80 3.2.1 Sample Sets for Evaluation of Instrument Performance 82 3.2.1.1 Ceramic Colour Standard – Series II (CCSII) 82 3.2.1.2 Ceram Gray Scale (CGS) 83 3.2.1.3 EBU 84 3.2.1.4 10 DuPont Paint Pairs 85 3.2.1.5 122 Metamer Set 86 3.2.1.6 ColorChecker® (CC) 87 3.2.1.7 Digital ColorChecker® Semi Gloss (SG) 88 3.2.2 Sample Sets for Development of Characterisation Models and Reflectance Estimation from Camera Responses 89 3.2.2.1 GretagMacbethTM ColorChecker® DC (MCDC) 89 3.2.2.2 Munsell Book of Color – Glossy Collection 90 3.2.2.3 Professional Colour Communicator (PCC) 92 3.2.3 Sample Sets for Spectral Representation and Determination of the Best Computational Method for Reflectance Estimation 93 3.2.3.1 Paint Group 94 3.2.3.1.1 DuPont SpectraMaster® 94 3.2.3.1.2 Munsell II (Munsell Limit Color Cascade) 94 3.2.3.1.3 NCS 95 3.2.3.1.4 DIN 95 3.2.3.1.5 SOCS – Paint 95 3.2.3.2 Graphic Group 96 3.2.3.2.1 Packaging Ink 96 3.2.3.2.2 SOCS – Graphic 96 3.2.3.2.3 SOCS – Photo 97 3.2.3.2.4 SOCS – Printer 97 3.2.3.3 Plastic Group 97 3.2.3.3.1 Industry Plastic 98 3.2.3.4 Textile Group 98 3.2.3.4.1 Industry Cotton 98 3.2.3.4.2 Pantone® Cotton 99 3.2.3.4.3 SOCS – Textile 99 3.2.3.5 Skin Group 99 3.2.3.5.1 Oulu Skin 100 3.2.3.5.2 RIT Skin 100 3.2.3.5.3 SOCS – Face 100 3.2.3.6 Natural Group 101 3.2.3.6.1 Natural I (Cheung, 2000) 101 3.2.3.6.2 Natural II (Westland et al., 2000) 102 Chapter 4 Inter-Instrument Agreement 103 4.1 Instruments 104 4.1.1 Measuring Reflectance 104 4.2 Data Collection for Performance Evaluation 105 4.3 Results and Discussion 106 4.3.1 Uniform Correction of the Camera System 106 4.3.2 Accuracy 107 4.3.3 Short Term Repeatability 109 4.3.4 Long Term Repeatability 110 4.3.5 Inter-Instrument Agreement 111 4.3.6 Relative Colour Difference 113 4.3.7 Sphere vs. 45oa:0o 113 4.4 Conclusions 114 Chapter 5 Development of Colorimetric Models and Colour Targets 116 5.1 Data Collections 117 5.2 Camera Characterisation Model 118 5.2.1 Order of the Polynomial Model 118 5.3 Colour Selections for the Training Target 119 5.3.1 Hardeberg Method 119 5.3.2 MAXMINC Method 120 5.3.3 The Colour Difference Iteration (CDI) Method 121 5.4 Comparison among Colour Selection Methods 123 5.5 Colour Selection Guideline 129 5.6 Conclusions 134 Chapter 6 Spectral Representation of Databases 135 6.1 Spectral Datasets 136 6.2 Spectral Representation 137 6.2.1 Basis Functions for an Individual Set 138 6.2.1.1 Spectral Representation of Paint Samples 140 6.2.1.2 Spectral Representation of Graphic Samples 143 6.2.1.3 Spectral Representation of Plastic Samples 146 6.2.1.4 Spectral Representation of Textile Samples 147 6.2.1.5 Spectral Representation of Skin Samples 149 6.2.1.6 Spectral Representation of Natural Samples 151 6.2.2 Development of a Set of Basis Functions for All Materials 153 6.2.2.1 Number of Basis Functions for Representing Material Groups 153 6.2.2.2 Selection of the Mixture Set to Represent All Spectra 154 6.2.2.3 Spectral Representation for All Materials 159 6.3 Conclusions 167 Chapter 7 Reflectance Estimation from Colorimetric Values 169 7.1 Reflectance Estimation Method 170 7.1.1 Model Performance Varied with Number of Basis Functions 172 7.1.2 Model Performance Varied with Number of Localised Training Samples 174 7.2 Methods Comparison 181 7.3 Conclusions 189 Chapter 8 Reflectance Estimation from Camera Responses 190 8.1 Spectral Characterisation Approaches 191 8.1.1 Finlayson et al.’s method 192 8.1.2 Pseudo-Inverse method 194 8.1.3 Two-stage method 194 8.2 Experiment 194 8.2.1 Finlayson et al.’s Spectral Sensitivity Functions 195 8.3 Methods Comparison 199 8.4 Conclusions 203 Chapter 9 Conclusions and Future Work 204 9.1 Conclusions 205 9.2 Future Work 209 References 210 Author Biography 221

    Alsam, A. and Finlayson, G. 2006. Reducing the number of calibration surfaces. In: IS&T/SID 14th Color Imaging Conference, Scottsdale, AZ. pp.170-174.
    ANSI. The ANSI accredited standards IT8.
    ASTM. 1985. Standard method for computing the colors of objects by using the CIE system. West Conshohocken, Philadelphia: ASTM International.
    ASTM. 1995. Standard practice for computing the colors of objects by using the CIE system. West Conshohocken, Philadelphia: ASTM International.
    ASTM. 1999. Standard terminology of appearance. West Conshohocken, Philadelphia: ASTM International.
    Babaei, V., Amirshahi, S. H. and Agahian, F. 2009. Reflectance reconstruction by adapting Wiener restoration method: using color difference values as weighting matrix. In: 11th Congress of the International Colour Association.
    Barnard, K. and Funt, B. 2002. Camera characterization for color research. Color Research and Application, 27(3), pp.152-163.
    Battle, D. R. 1997. The measurement of colour. In: R. MCDONALD, ed. Colour Physics for Industry. 2 ed. Bradford: Society of Dyers and Colourists.
    Berns, R. S., Alman, D. H., Reniff, L., Snyder, G. D. and Balononrosen, M. R. 1991. Visual determination of suprathreshold color-difference tolerances using probit analysis. Color Research and Application, 16(5), pp.297-316.
    Bjerhammar, A. 1951. Application of calculus of matrices to the method of least-squares with special reference to geodetic calculations. Trans Roy Inst Technol Stockholm, 49.
    Bochko, V., Tsumura, N. and Miyake, Y. 2007. Spectral color imaging system for estimating spectral reflectance of paint. Journal of Imaging Science and Technology, 51(1), pp.70-78.
    Buchsbaum, G. and Gottschalk, A. 1984. Chromaticity coordinates of frequency-limited functions. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 1(8), pp.885-887.
    Burns, P. D. 1997. Analysis of Image Noise in Multispectral Color Acquisition. PhD thesis, Rochester Institute of Technology.
    Burns, P. D. and Berns, R. S. 1996. Analysis multispectral image capture. In: IS&T/SID 4th Color Imaging Conference, pp.19-22.
    Chatzis, I. S., Kappatos, V. A. and Dermatas, E. S. 2006. Filter selection for multi-spectral image acquisition using the feature vector analysis methods. In: D. T. PHAM, E. E. ELDUKHRI and A. J. SOROKA, eds. Intelligent Production Machines and Systems. Oxford: Elsevier Science Ltd, pp.283-288.
    Cheung, V. 2000. Colour statistics of natural surfaces. MSc thesis, University of Derby.
    Cheung, V. and Westland, S. 2004a. Color selections for characterization charts. In: Aachen, Germany. The Second European Conference on Colour Graphics, Imaging and Vision (CGIV), pp.116-119.
    Cheung, V. and Westland, S. 2006. Methods for optimal color selection. Journal of Imaging Science and Technology, 50(5), pp.481-488.
    Cheung, V., Westland, S., Connah, D. and Ripamonti, C. 2004b. A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms. Coloration Technology, 120(1), pp.19-25.
    Cheung, V., Westland, S., Li, C. J., Hardeberg, J. and Connab, D. 2005. Characterization of trichromatic color cameras by using a new multispectral imaging technique. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 22(7), pp.1231-1240.
    Chiao, C. C., Cronin, T. W. and Osorio, D. 2000. Color signals in natural scenes: Characteristics of reflectance spectra and effects of natural illuminants. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 17(2), pp.218-224.
    CIE. 1978. Recommendations on uniform colour spaces, colour difference equations, psychometrics colour terms. Supplement No. 2 of CIE Publication 15 (E1-1.3.1).
    CIE. 1987. International lighting vocabulary. CIE Publication No. 17.4.
    CIE. 1989. Special metamerism index: observer metamerism. CIE Publication No. 80, Vienna, Austria.
    CIE. 1991a. CIE Colorimetry -- Part1: Standard colorimetric observers. ISO/CIE 10527, CIE S 014-1/E.
    CIE. 1991b. CIE Colorimetry -- Part 2: Standard illuminants for colorimetry
    CIE. 1995. Industrial colour-difference evaluation. CIE Publication 116, Vienna.
    CIE. 2004. Colorimetry. CIE Publication No.15.3, Vienna: CIE Technical Report.
    Clarke, F. J. and Malkin, F. 1981. Development of a new series of ceramic colour standards. Journal of the Society of Dyers and Colourists, 97(12), pp.503-504.
    Clarke, F. J. J. 1969. Ceramic colour standards - an aid for industrial colour control. Printing Technology Magazine, 13(3), pp.101-113.
    Clarke, F. J. J., Mcdonald, R. and Rigg, B. 1984. Modification to the JPC79 colour-difference formula. Journal of the Society of Dyers and Colourists, 100(4), pp.128-132.
    Cleland, T. M. 1921. A practical description of the Munsell colour system with suggestions for its use. Munsell Color Company.
    Cohen, J. 1964. Dependency of the spectral reflectance curves of the Munsell color chips. Psychonomic Science, 1(12), pp.369-370.
    Connah, D., Alsam, A. and Hardeberg, J. Y. 2004a. Multispectral imaging: How many sensors do we need? In: IS&T/SID 12th Color Imaging Conference, pp.53-58.
    Connah, D., Hardeberg, J. Y. and Westland, S. 2004b. Comparison of linear spectral reconstruction methods for multispectral imaging. Icip: 2004 International Conference on Image Processing, Vols 1- 5, pp.1497-1500.
    Dalton, C. and Peters, J. J. 1988. Real sample sets for camera colour-rendering measurement. EBU Review - Technical No. 227.
    Dannemiller, J. L. 1992. Spectral reflectance of natural objects - how many basis functions are necessary. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 9(4), pp.507-515.
    Datacolor. 2007. Datacolor 650/600/400 user's guide.
    Davis, R. and Gibson, K. S. 1931. Filters for the reproduction of sunlight and daylight and the determination of color temperature. Precision Measurement and Calibration (National Bureau of Standards), 10, pp.641-805.
    Derby, R. E. J. 1983. Color technology in the textile industry Research Triangle Park, NC: American Association of Textile Chemists and Colorists.
    DuPontTM, SpectraMaster® Color Atlas.
    EBU. 1983a. Technical Document 3237 Supplement 1 second edition: Methods of measurement of the colorimetric fidelity of television camera: Measurement procedures.
    EBU. 1983b. Technical Document 3238: Methods of measuring the main characteristics of television cameras.
    Eem, J. K., Shin, H. D. and Park, S. O. 1994. Reconstruction of surface spectral reflectances using characteristic vectors of munsell colors. IS&T/SID 2nd Color Imaging Conference, pp.127-131.
    Fairchild, M. D. 2005. Color appearance models. Chichester: Wiley.
    Fairman, H. S. 1995. Results of the ASTM field test of tristimulus weighting functions. Color Research and Application, 20(1), pp.44-49.
    Fairman, H. S. and Brill, M. H. 2004. The principal components of reflectances. Color Research and Application, 29(2), pp.104-110.
    Fairman, H. S., Brill, M. H. and Hemmendinger, H. 1997. How the CIE 1931 color-matching functions were derived from Wright-Guild data. Color Research and Application, 22(1), pp.11-23.
    Farrell, J. E. and Wandell, B. A. 1993. Scanner linearity. Journal of Electronic Imaging, 2(3), pp.225-230.
    Finlayson, G. D., Hordley, S. and Hubel, P. M. 1998. Recovering device sensitivities with quadratic programming. In: Scottsdale, AZ. pp.90-95.
    Finlayson, G. D. and Morovič, P. M. 1999. Metamer constrained colour correction. In: IS&T/SID 7th Color Imaging Conference, Scottsdale, AZ. pp.26-31.
    Flanklin, P. 1982. Interpolation methods and apparatus. Patent number: 4,334,240.
    Foster, D. H., Amano, K., Nascimento, S. M. C. and Foster, M. J. 2005. Incidence of metamerism in natural scenes. In: Baltimore, MD. pp.36-39.
    Foster, D. H., Amano, K., Nascimento, S. M. C. and Foster, M. J. 2006. Frequency of metamerism in natural scenes. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 23(10), pp.2359-2372.
    Foster Jr, W. H., Gans, R., Sterns, E. I. and Stearns, R. E. 1970. Weights for calculation of tristimulus values from sixteen reflectance values. Color Eng, 8(3), pp.35-47.
    García-Beltrán, A., Nieves, J. L., Hernández-Andrés, J. and Romero, J. 1998. Linear bases for spectral reflectance functions of acrylic paints. Color Research and Application, 23(1), pp.39-45.
    Golub, G. H. and Van Loan, C. F. 1996. Matrix computations. 3rd ed. Baltimore: Johns Hopkins University Press.
    Green, P. 1999. Understanding digital color. 2nd ed. Sewickley, PA: Graphic Arts Technical Foundation.
    Green, P. 2002a. Overview of characterization methods. Colour engineering: achieving device independent colour. Chichester: Wiley.
    Green, P. 2002b. Overview of characterization methods. In: P. GREEN and L. MACDONALD, eds. Colour engineering: achieving device independent colour. Chichester: Wiley, pp.127-141.
    Guild, J. 1931. The colorimetric properties of the spectrum. Philos. Trans. R. Soc. London, Ser. A, 230, pp.149-187.
    Hallikainen, J., Parkkinen, J. and Jaaskelainen, T. 1988. Acousto-optic color spectrometer. Review of Scientific Instruments, 59(1), pp.81-83.
    Haneishi, H., Hasegawa, T., Hosoi, A., Yokoyama, Y., Tsumura, N. and Miyake, Y. 2000. System design for accurately estimating the spectral reflectance of art paintings. Applied Optics, 39(35), pp.6621-6632.
    Haneishi, H., Hasegawa, T., Tsumura, N. and Miyake, Y. 1997. Design of color filters for recording artworks. Proc. of IS&T's 50th Annual Conference, pp.369-372.
    Hardeberg, J. Y. ed. 1999. Acquisition and reproduction of color images: Colorimetric and multispectral approaches. Paris, France: Ecole Nationale Superieure des Telecommunications.
    Hardeberg, J. Y. 2002. On the spectral dimensionality of object colours. In: 1st European Conference on Colour in Graphics, Imaging, and Vision, Poitiers. pp.480-485.
    Hardeberg, J. Y. 2004. Filter selection for multispectral color image acquisition. Journal of Imaging Science and Technology, 48(2), pp.105-110.
    Hardeberg, J. Y., Brettel, H. and Schmitt, F. 1998. Spectral characterisation of electronic cameras. In: Zurich, Switzerland. Electronic Imaging: Processing, Printing, and Publishing in Color, pp.100-109.
    Hardeberg, J. Y., Schmitt, F. and Brettel, H. 2002. Multispectral color image capture using a liquid crystal tunable filter. Optical Engineering, 41(10), pp.2532-2548.
    Hernandez-Andres, J., Romero, J. and Lee, R. L. 2001. Colorimetric and spectroradiometric characteristics of narrow-field-of-view clear skylight in Granada, Spain. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 18(2), pp.412-420.
    Hong, G. W., Luo, M. R. and Rhodes, P. A. 2001. A study of digital camera colorimetric characterization based on polynomial modeling. Color Research and Application, 26(1), pp.76-84.
    Horn, B. K. P. 1984. Exact reproduction of colored images. Computer Vision Graphics and Image Processing, 26(2), pp.135-167.
    Hunt, R. W. G. 1998. Measuring colour. 3rd ed. Kingston-upon-Thames: Fountain Press.
    Hunter, R. S. 1942. Photoelectric tristimulus colorimetry with three filters. Journal of the Optical Society of America, 32(9), pp.509-538.
    Hunter, R. S. and Harold, R. W. 1987. The measurement of appearance. 2nd ed. New York ; Chichester: Wiley.
    Imai, F. H. and Berns, R. S. 1999a. A comparative analysis of spectral reflectance reconstruction in various spaces using a trichromatic camera system. In: IS&T/SID 7th Color Imaging Conference, pp.21-25.
    Imai, F. H. and Berns, R. S. 1999b. Spectral estimation using trichromatic digital cameras. In: Proceedings of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives, pp.42-49.
    Imai, F. H. and Berns, R. S. 2001a. Spectral estimation of artist oil paints using multi-filter trichromatic imaging. In: Rochester, NY. pp.504-507.
    Imai, F. H., Berns, R. S. and Tzeng, D. 2000. A Comparative analysis of spectral reflectance estimated in various spaces using a trichromatic camera system. Journal of Imaging Science and Technology, 44(4), pp.280-287.
    Imai, F. H., Quan, S., Rosen, M. R. and Berns, R. S. 2001b. Digital camera filter design for colorimetric and spectral accuracy. In: 3rd International Conference on Multispectral Color Science, pp.13-16.
    Imai, F. H., Rosen, M. R. and Berns, R. S. 2001c. Multi-spectral imaging of van Gogh's Self-portrait at the National Gallery of Art, Washington, D.C. In: Montreal, Que., pp.185-189.
    Imai, F. H., Rosen, M. R. and Berns, R. S. 2002. Comparative study of metrics for spectral match quality. In: 1st European Conference on Colour in Graphics, Imaging, and Vision, Poitiers. pp.492-496.
    Imai, F. H., Tsumura, N., Haneishi, H. and Miyake, Y. 1996a. Principal component analysis of skin color and its application to colorimetric color reproduction on CRT display and hardcopy. Journal of Imaging Science and Technology, 40(5), pp.422-430.
    Imai, F. H., Tsumura, N., Haneishi, H. and Miyake, Y. 1996b. Spectral reflectance of skin color and its applications to color appearance modeling. IS&T/SID 4th Color Imaging Conference, pp.121-124.
    ISO. 1996. Graphic technology -- Prepress digital data exchange -- Input data for characterization of 4-colour process printing. ISO 12642.
    ISO. 1997a. Graphic technology -- Prepress digital data exchange -- CMYK standard colour image data (CMYK/SCID). ISO 12640.
    ISO. 1997b. Graphic technology -- Prepress digital data exchange -- Colour targets for input scanner calibration. ISO 12641.
    Jaaskelainen, T., Parkkinen, J. and Toyooka, S. 1990. Vector-subspace model for color representation. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 7(4), pp.725-730.
    Johnson, T. 1996. Methods for characterizing colour scanners and digital cameras. Displays, 16(4), pp.183-191.
    Jolliffe, I. T. 1986. Principal component analysis. New York: Springer.
    Jones, M. J. and Rehg, J. M. 2002. Statistical color models with application to skin detection. International Journal of Computer Vision, 46(1), pp.81-96.
    JSA. 1998. Graphic Technology-Standard object color spectra database for colour reproduction evaluation. Information Processing Divisional Council, Japanese Standards Association.
    Judd, D. B. 1949. A comparison of direct colorimetry of titanium pigments with their indirect colorimetry based on spectrophotometry and a standard observer. Journal of the Optical Society of America, 39(11), pp.945-950.
    Kamimura, K., Tsumura, N., Nakaguchi, T. and Miyake, Y. 2005. Evaluation and analysis for spectral reflectance image of human skin. In: San Jose, CA. pp.30-37.
    Kanamori, K., Fumoto, T. and Kotera, H. 1992. A color transformation algorithm using prism interpolation. In: 8th International Congress on Advances in Non-Impact Printing Technologies, Oct 25-30, Williamsburg, Va. SPRINGFIELD: Soc Imaging Science & Technology, pp.477-482.
    Kanamori, K., Kotera, H., Yamada, O., Motomura, H., Iikawa, R. and Fumoto, T. 1993. Fast color processor with programmable interpolation by small memory (PRISM). Journal of Electronic Imaging, 2(3), pp.213-224.
    Kang, H. R. 1997. Color technology for electronic imaging devices. Bellingham, Wash., USA: SPIE Optical Engineering Press.
    Kelly, K. L., Gibson, K. S. and Nickerson, D. 1943. Tristimulus specification of the Munsell Book of Color from spectrophotometric measurements. Journal of the Optical Society of America, 33(7), pp.355-375.
    Keusen, T. 1996. Multispectral color system with an encoding format compatible with the conventional tristimulus model. Journal of Imaging Science and Technology, 40(6), pp.510-515.
    Keusen, T. and Praefcke, W. 1995. Multispectral color system with an encoding format compatible to the conventional tristimulus model. Proceedings of the Color Imaging Conference: Color Science, Systems, and Applications, pp.112-114.
    Kim, D. H. and Nobbs, J. H. 1997. New weighting functions for the weighted CIELAB colour difference formula. Proc Colour 97 Kyoto, 1, pp.446-449.
    Kohonen, O., Parkkinen, J. and Jaaskelainen, T. 2006. Databases for spectral color science. Color Research and Application, 31(5), pp.381-390.
    Kotera, H. 1993. A single chip color processor for device independent color reproduction. IS&T/SID 1st Color Imaging Conference, pp.133-137.
    Krinov, E. L. 1947. Spectral reflectance of natural objects. Ottawa: National Research Council of Canada.
    Kuehni, R. G. 2002. The early development of the Munsell system. Color Research and Application, 27(1), pp.20-27.
    Kuehni, R. G. 2005. The CMC(l:c) color diference formula and the values for the weights l and c. AATCC Review, 5(11), p26.
    Kuo, W. G. and Luo, M. R. 1996a. Methods for quantifying metamerism. Part 1 - Visual assessment. Journal of the Society of Dyers and Colourists, 112(11), pp.312-320.
    Kuo, W. G. and Luo, M. R. 1996b. Methods for quantifying metamerism. Part 2 - Instrumental methods. Journal of the Society of Dyers and Colourists, 112(12), pp.354-360.
    Laamanen, H., Jaaskelainen, T. and Parkkinen, J. P. S. 2000. Comparison of PCA and ICA in color recognition. Proceedings of SPIE - The International Society for Optical Engineering, 4197, pp.367-377.
    Lenz, R., sterberg, M., Hiltunen, J., Jaaskelainen, T. and Parkkinen, J. 1995. Unsupervised filtering of color spectra. Proceedings of the 9th Scandinavian Conference on Image Analysis, pp.803-810.
    Lenz, R., sterberg, M., Hiltunen, J., Jaaskelainen, T. and Parkkinen, J. 1996. Unsupervised filtering of color spectra. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 13(7), pp.1315-1324.
    Li, C. J., Cui, G. and Luo, M. R. 2003a. The accuracy of polynomial models for characterising digital cameras. In: Proceedings of International Colour Association, pp.166-170.
    Li, C. J., Cui, G. and Luo, M. R. 2003b. The accuracy of polynomial models for characterising digital cameras. In: Bangkok, Thailand. Proceedings of Midterm meeting of International Colour Association (AIC), pp.166-170.
    Li, C. J. and Luo, M. R. 2001. The estimation of spectral reflectances using the smoothness constraint condition. In: IS&T/SID 9th Color Imaging Conference, Scottsdale, AZ. pp.62-67.
    Li, C. J. and Luo, M. R. 2005. How many basis vectors can be used for generating reflectance? In: AIC Color 2005, May 8-13, Granada, Spain. pp.1637-1640.
    Li, C. J., Luo, M. R. and Rigg, B. 2004. A new method for computing optimum weights for calculating CIE tristimulus values. Color Research and Application, 29(2), pp.91-103.
    Li, X., Li, C. J., Luo, M. R., Pointer, M., Cho, M. and Kinf, J. 2007. A new colour gamut for object colours. In: Albuquerque, NM. pp.283-287.
    Luo, M. R. 1998. Colour science. In: S. J. SANGWINE and R. E. N. HORNE, eds. The Colour Image Processing Handbook. pp.26-66.
    Luo, M. R. 1999. Colour science: Past, present and future. In: L. W. MACDONALD and M. R. LUO, eds. Colour Imaging: Vision and Technology. Chichester: Wiley.
    Luo, M. R. 2001. The CIE 2000 colour difference formula: CIEDE2000. In: 9th Congress of the International Colour Association, Rochester, NY. pp.554-559.
    Luo, M. R. 2002. Development of colour-difference formulae. Review of Progress in Coloration and Related Topics, 32, pp.28-39.
    Luo, M. R., Cui, G. H. and Dakin, J. 2002. Applying digital cameras for measuring colour. In: AIC Color 2002 SI, Color and Textiles, August 29-31, pp.121-127.
    Luo, M. R. and Rigg, B. 1986. Chromaticity-discrimination ellipses for surface colors. Color Research and Application, 11(1), pp.25-42.
    Macadam, D. L. 1942. Visual sensitivities to color differences in daylight. Journal of the Optical Society of America, 32(5), pp.247-274.
    Macadam, D. L. 1974. Uniform color scales. Journal of the Optical Society of America, 64(12), pp.1691-1702.
    Macdonald, L. and Ji, W. 2002. Colour characterisation of a high-resolution digital camera. In: Poitiers. pp.433-437.
    Mahy, M. 2000. Analysis of color targets for output characterization. In: Scottsdale, AZ. pp.348-355.
    Maitre, H., Schmitt, F., Crettez, J. P., Wu, Y. F. and Hardeberg, J. Y. 1996. Spectrophotometric image analysis of fine art paintings. In: IS&T/SID 4th Color Imaging Conference, pp.50-53.
    Malkin, F., Larkin, J. A., Verrill, J. F. and Wardman, R. H. 1997. The BCRA-NPL ceramic colour standards, series II - Master spectral reflectance and thermochromism data. Journal of the Society of Dyers and Colourists, 113(3), pp.84-94.
    Maloney, L. T. 1986. Evaluation of linear models of surface spectral reflectance with small numbers of parameters. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 3(10), pp.1673-1683.
    Maloney, L. T. and Wandell, B. A. 1986. Color constancy - a method for recovering surface spectral reflectance. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 3(1), pp.29-33.
    Mansouri, A., Sliwa, T., Hardeberg, J. Y. and Voisin, Y. 2008. Representation and estimation of spectral reflectances using projection on PCA and wavelet bases. Color Research and Application, 33(6), pp.485-493.
    Mardia, K. V., Kent, J. T. and Bibby, J. M. 1979. Multivariate analysis. London: Academic Press.
    Marszalec, E., Martinkauppi, B., Soriano, M. and Pietikäinen, M. 2000. Physics-based face database for color research. Journal of Electronic Imaging, 9(1), pp.32-38.
    Martinez-Verdu, F., Pujol, J. and Capilla, P. 2003. Characterization of a digital camera as an absolute tristimulus colorimeter. Journal of Imaging Science and Technology, 47(4), pp.279-295.
    Martinkauppi, B. 2002. Face colour under varying illumination-analysis and applications. PhD thesis.
    Mccamy, C. S., Marcus, H. and Davidson, J. G. 1976. Color-redition chart. J Appl Photogr Eng, 2(3), pp.95-99.
    Meyer Jr, C. D. 1973. Generalized inverses and ranks of block matrices. SIAM J. Appl. Math., 25, pp.597-602.
    Moore, E. H. 1920. On the reciprocal of the general algebraic matrix. Bulletin of the American Mathematical Society, 26, pp.394-395.
    Morovǐc, J., Arnabat, J., Richard, Y. and Albarrán, . 2010. Sampling optimization for printer characterization by greedy search. Ieee Transactions on Image Processing, 19(10), pp.2705-2711.
    Munsell Color. 1976a. Munsell Book of Color - Glossy collection. Baltimore, MD: Munsell Color, Macbeth Division, Kollmorgen Corporation.
    Munsell Color. 1976b. Munsell Book of Color - Matte finish collection. Baltimore, MD: Munsell Color, Macbeth Division, Kollmorgen Corporation.
    NCS. 1979. Swedish Standard SS 01 91 02, Colour Atlas. Stockholm, Sweden: Swedish Standard Institution.
    Newhall, S. M., Nickerson, D. and Judd, D. B. 1943. Final report of the O.S.A. subcommittee on the spacing of the Munsell colors. Journal of the Optical Society of America, 33(7), pp.385-411.
    Nickerson, D. 1940. History of the Munsell Color System and its scientific application. Journal of the Optical Society of America, 30(12), pp.575-586.
    NIKON. 2006. Nikon Corporation. The Nikon guide to digital photography with the D80 digital camera. Tokyo: Japan.
    Novati, G., Pellegri, P. and Schettini, R. 2004. Selection of filters for multispectral acquisition using the filter vectors analysis method. In: Color Imaging IX: Processing, Hardcopy, and Applications, pp.20-26.
    NPL. 2009. Certificate of calibration, calibration of set 0902 ceramic colour standards, series II by comparison with a NPL calibrated set of reference standards using a spectraflash spectrophotometer.
    Ohta, N. and Robertson, A. R. 2005. Colorimetry: Fundamentals and applications. Chichester: Wiley.
    Ojima, N., Haneishi, H. and Miyake, Y. 1993. The appearance of skin with make-up (II). J. Soc. Photogr. Sci. Technol. Japan, 56, pp.264-269.
    Park, J. and Park, K. M. 1994. Professional colour communicator (PCC) - the definitive colour selector. Book of Papers - Aatcc 1994 International Conference & Exhibition, pp.294-296.
    Parkkinen, J. P. S., Hallikainen, J. and Jaaskelainen, T. 1989. Characteristic spectra of Munsell colors. Journal of the Optical Society of America a-Optics Image Science and Vision, 6(2), pp.318-322.
    Penrose, R. 1955. A generalized inverse for matrices. In: Proceedings of the Cambridge Philosophical Society, pp.406-413.
    Peres, M. R. 2007. Focal encyclopedia of photography : digital imaging, theory and applications, history, and science. Amsterdam ; London: Focal.
    Pointer, M. R. 1980. The gamut of real surface colors. Color Research and Application, 5(3), pp.145-155.
    Praefcke, W. 1996. Transform coding of reflectance spectra using smooth basis vectors. Journal of Imaging Science and Technology, 40(6), pp.543-548.
    Pugsley, P. C. 1974. Image reproduction methods and apparatus. Patent number: 3,893,166.
    Randall, D. 1998. Instruments for the measurement of color. Textile Chemist and Colorist, 30(2), pp.20-26.
    Richter, M. 1955. The official German standard color chart. Journal of the Optical Society of America, 45(3), pp.223-226.
    Richter, M. and Witt, K. 1986. The story of the Din color system. Color Research and Application, 11(2), pp.138-145.
    Rigg, B. 1997. Colorimetry and the CIE system. In: R. MCDONALD, ed. Colour Physics for Industry. 2 ed. Bradford: Society of Dyers and Colourists.
    Romero, J., García-Beltrán, A. and Hernández-Andrés, J. 1997. Linear bases for representation of natural and artificial illuminants. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 14(5), pp.1007-1014.
    Romney, A. K. 2008. Relating reflectance spectra space to Munsell color appearance space. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 25(3), pp.658-666.
    Romney, A. K. and Indow, T. 2003. Munsell reflectance spectra represented in three-dimensional Euclidean space. Color Research and Application, 28(3), pp.182-196.
    Sakamoto, T. and Itooka, A. 1978. Interpolation method for memory devices. Patent number: 53-123201.
    Saunders, D. and Cupitt, J. 1993. Image processing at the national gallery: The VASARI project. National Gallery Technical Bulletin, 14, pp.72-85.
    Schanda, J. 2007. Colorimetry: Understanding the CIE system.
    Shen, H. L., Cai, P. Q., Shao, S. J. and Xin, J. H. 2007a. Reflectance reconstruction for multispectral imaging by adaptive Wiener estimation. Optics Express, 15(23), pp.15545-15554.
    Shen, H. L. and Xin, J. H. 2004. Spectral characterization of a color scanner by adaptive estimation. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 21(7), pp.1125-1130.
    Shen, H. L., Xin, J. H. and Shao, S. J. 2007b. Improved reflectance reconstruction for multispectral imaging by combining different techniques. Optics Express, 15(9), pp.5531-5536.
    Shi, M. H. and Healey, G. 2002. Using reflectance models for color scanner calibration. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 19(4), pp.645-656.
    Sobagaki, H., Takahama, K. and Nayatani, Y. 1989. Estimation of spectral reflectance functions for Munsell renotations. In: 6th Congress of the International Colour Association, Buenos Aires. pp.156-158.
    Speranskaya, N. I. 1959. Determination of spectrum color co-ordinates for twenty-seven normal observers. Optics and Spectroscopy, 7, pp.424-428.
    Stearns, E. I. 1985. Calculation of tristimulus values and weights with the revised CIE recommendations. Textile Chemist and Colorist, 17(8), pp.162-168.
    Stiles, W. S. 1958. The average colour-matching functions for a large matching field. Visual Problems of Color Symposium: Volume 1. London: Her Majesty's Stationery Office, pp.209-247.
    Stiles, W. S. and Burch, J. M. 1959. NPL colour-matching investigation: final report. Optica Acta, 6(6), pp.1-26.
    Styles, L. B. 2008. Selection of optimal filters for multispectral imaging. Applied Optics, 47(30), pp.5585-5591.
    Sun, Q. and Fairchild, M. 2001a. A new procedure for capturing spectral images of human portraiture. Proceedings of the 9th Congress of the International Colour Association, AIC Color 2001.
    Sun, Q. and Fairchild, M. D. 2001b. Statistical characterization of spectral reflectances in spectral imaging of human portraiture. In: Scottsdale, AZ. pp.73-79.
    Sun, Q. and Fairchild, M. D. 2002. Statistical characterization of face spectral reflectances and its application to human portraiture spectral estimation. Journal of Imaging Science and Technology, 46(6), pp.498-506.
    Tajima, J., Haneishi, H., Ojima, N. and Tsukada, M. 2002. Representative data selection for standard object colour spectra database (SOCS). In: Scottsdale, AZ. pp.155-160.
    Tajima, J., Tsukada, M., Miyake, Y., Haneishi, H., Tsumura, N., Nakajima, M., Azuma, Y., Iga, T., Inui, M., Ohta, N., Ojima, N. and Sanada, S. 1998. Development and standardization of a spectral characteristics data base for evaluating color reproduction in image input devices. In: Zurich. pp.42-50.
    Thomson, M. and Westland, S. 2002. Spectral colour statistics of surfaces. In: L. W. MACDONALD and M. R. LUO, eds. Colour image science : exploiting digital media. Chichester: Wiley.
    Tonnquist, G. 1986. Das Natürliche Farbsystem NCS. pp.462-469.
    Vantrigt, C. 1990a. Smoothest reflectance functions. I. Definition and main results. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 7(10), pp.1891-1904.
    Vantrigt, C. 1990b. Smoothest reflectance functions. II. Complete results. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 7(12), pp.2208-2222.
    Venable, W. H. 1989. Accurate tristimulus values from spectral data. Color Research and Application, 14(5), pp.260-267.
    Verivide. 2009. The DigiEye colour measurement & imaging system.
    Vrhel, M. J., Gershon, R. and Iwan, L. S. 1994. Measurement and analysis of object reflectance spectra. Color Research and Application, 19(1), pp.4-9.
    Wandell, B. A. 1982. Measurement of small color differences. Psychological Review, 89(3), pp.281-302.
    Wang, H., Cui, G., Luo, R. and Xu, H. 2008. Evaluation of colour-difference formulae for different colour-difference magnitudes. In: 4th European Conference on Colour in Graphics, Imaging, and Vision, Terrassa, Spain. Society for Imaging Science and Technology, pp.89-92.
    Westland, S. 2002. Colour science. In: D. ROBERTS, ed. Signals and Perception: The Fundamentals of Human Sensation. Basingstoke: Palgrave Macmillan.
    Westland, S. and Ripamonti, C. 2004. Computational colour science using Matlab. Chichester: J. Wiley.
    Westland, S., Shaw, J. and Owens, H. 2000. Colour statistics of natural and man-made surfaces. Sensor Review, 20(1), pp.50-55.
    Williamson, C. J. 1999. Durability and cleaning of matt surface ceramic colour standards. Analytica Chimica Acta, 380(2-3), pp.413-416.
    Witt, K. 1999. Geometric relations between scales of small colour differences. Color Research and Application, 24(2), pp.78-92.
    Wright, W. D. 1928. A trichromatic colorimeter with spectral primaries. Transactions of the Optical Society, 29(5), pp.225-242.
    Wright, W. D. 1929. A re-determination of the trichromatic coefficients of the spectral colours. Transactions of the Optical Society, 30(4), pp.141-164.
    Wright, W. D. 1941. The sensitivity of the eye to small colour differences. Proceedings of the Physical Society, 53, pp.93-112.
    Wyszecki, G. and Stiles, W. S. 1982. Color science: Concepts and methods, quantitative data and formulae. New York: Wiley.
    X-Rite. 2007. Color-Eye 7000A specification.
    X-Rite. 2009. Color I7 benchtop spectrophotometer operation manual.
    X-Rite. 2011. SpectroEye spectrophotometer specification.
    Yokoyama, Y., Tsumura, N., Haneishi, H., Miyake, Y., Hayashi, J. and Saito, M. 1997. New color management system based on human perception and its application to recording and reproduction of art paintings. Proceedings of the Color Imaging Conference: Color Science, Systems, and Applications, pp.169-172.

    QR CODE