傳楸善臺灣大學：電機工程學研究所哈小美Chikane, VarshaVarshaChikane2007-11-262018-07-062007-11-262018-07-062004http://ntur.lib.ntu.edu.tw//handle/246246/53216For many decades traditional cameras are used for taking photographs, however nowadays consumers and users of the traditional cameras are more concerned about the quality as well as quantity of the pictures, the use of traditional cameras creates some limitations on both quality and quantity. In the recent years digital cameras have captured the camera market. Although quality and quantity factors are considered, but consumers are more nostalgic about the quality of the picture which is a complex subject involving exposure accuracy, color fidelity, optics, and image compression techniques, where color fidelity is affected by several factors which include automatic white balance.Chapter 1 Introduction……………………………………………………..1 1.1 Pixels…………………………………………………………………………………...1 1.2 Color Temperature………………………………………………………………..........2 1.3 Spectral Power distribution………………………………………………………….....2 1.4 Color Constancy……………………………………………………………………….4 1.5 Advantage of b rC YC Color Space over RGB Color Space………………………...….4 Chapter 2 Basic Methods for Automatic White Balance………………...5 2.1 Gray World Assumption (GWA)………………………………………………...........5 2.2 Perfect Reflector Assumption (PRA)……………………………………………….....7 2.3 Fuzzy Rule Method (FRM)…………………………………………………………....9 2.3.1 Experiment...........................................................................................................10 Chapter 3 Chiou’s White Balance Method……………………………....14 3.1 White Point Detecting Unit………………………………………………………..…14 3.2 The White Balance Judging Unit………………………………………………….....18 3.3 The White Balance Adjusting Unit………………………………………………..…20 Chapter 4 White Balance……………………………………………........23 4.1 White Point Detection……………………………………………………………..…23 4.1.1 Influence of Light Source on Scene Colors…………………………………....23 4.1.2 Some Basic Methods Used for White Point Detection……………………..….24 Chapter 5 Method for Cr - Cb Range Minimization…………………….27 5.1 Histogram Equalization……………………………………………………………...27 5.1.1 Histogram Equalization of Gray-level Image………………………………….27 5.1.2 Histogram Equalization of Color Image…………………………………….…28 Chapter 6 White Point Detection…………………………………….......31 6.1 Chromaticity Values…………………………………………………………………31 6.2 White Point Detection……………………………………………………………......31 6.2.1 Brightest Pixel………………………………………………………………….31 6.2.2 Detection of Group of White Pixels………………………………………........33 Chapter 7 White Balance Adjustment………………………………..….34 7.1 Scale factors………………………………………………………………………….34 7.1.1 Scale Factors According to the White Point………………………………...…34 7.1.2 Scale Factors According to the GWA………………………………………….34 7.1.3 Selection of Scale Factors According to Color Cast………………...…………35 Chapter 8 Our Method……………………………………………..…….36 8.1 Overview of Our Method…………………………………………………………….36 8.1.1 White Object Purification……………………………………………...………36 8.1.2 White Point Detection………………………………………………………….37 8.1.3 White Balance Adjustment…………………………………………………….40 Chapter 9 Experimental Results…………………………………...…….42 9.1 Simulation Methods………………………………………………………………….42 9.2 Camera Specifications……………………………………………………………….42 9.3 Light Sources………………………………………………………………………...42 9.4 Test Images…………………………………………………………………………..43 9.4.1 Under Standard Light Sources………………………………………………...44 9.4.2 Natural and Household Light Sources………………………………………...46 9.4.3 Images of Varying Object Situations.................................................................47 9.5 Visual Results of Simulations..………………………………………………...……48 9.6 Evaluative Values of Simulations……………………………………………………68 9.7 Complexity…………………………………………………………………………...69 Chapter 10 Conclusions and Future Work...............................................71 10.1 Conclusions…………………………………………………………………...…….71 10.2 Future Work………………………………………………………………...………72 References……………………………………………………………..…..73en-US白平衡white balancethesis