臺灣博碩士論文加值系統

大約每十二個男性中一位有某種程度上的色盲。目前沒有任何有效的方法可以治療色盲，雖然已經有一些技巧可以幫助色盲辨識顏色，像是使用色盲矯正鏡片。但這些方法也有他的危險性，長期依賴使用可能會造成使用者視覺敏銳度降低或者景深感損失。但現今大量的資訊透過網路以多媒體的形式來傳達，而色彩也因而成為一個傳遞資料的重要角色，但同時某種程度上地妨礙一些較嚴重的色盲取得信息。本篇論文提供了一個色盲的輔助處理，這個輔助技術主要藉將原影像色彩的資訊有效的利用並重建在色盲所能見到的色域。此技術經由一些色盲模擬系統來驗證結果，此外論文中也比較了其他不同的輔助方法並討論個別的優缺。
本論文的後半則著重在彩色影像的加強。我們提出了兩個分別在CIE xyY和CIE L*u*v*色彩座標上的色彩加強技術。此技術和其他技術最大的不同在於考量到了彩度和亮度上的的相關性，故不會造成常見的失真。這個加強處理也可搭配其他亮度處理來應用。另外我們提了一個背景調色技術與先前的色彩加強處理來恢復古代畫作。

Approximately one man out of twelve has some degree of color deficiency. There is no cure for color vision deficiency. Though there are some techniques trying to help them distinguish color, such as tinted spectacles and monocular contact lenses, however, these devices might boil down to further serious situation, such as impaired visual acuity, visual distortions, and diminishing the depth perception. However, vision is the one that we rely on most to access information. Nowadays, for the development of technology, people acquire quite many facts from multimedia. Hence, color also play a role in conveying information and hence obstruct some color deficient people to some degree. Hence, this thesis offers assistance processes to help color deficient people distinguish colors. This assistance algorithm is based on utilizing the color gamut seen by color deficient people. The effect of the proposed assistance process is proved by examine the enhanced image through the color deficient vision simulation in [4]. Besides, other assistance processes are compared with the proposed one.
In the later of the thesis, we focus on contrast enhancement on ordinary images. We proposed the saturation enhancement methods without hue and luminance changes in CIE xyY and CIE L*u*v*. The main contribution of this part is that we take the dependence of luminance and chromaticity into consideration. Hence, the image artifacts and color distortion, which other saturation enhancement would results in, are not produced through the proposed saturation enhancement. Furthermore, the proposed saturation enhancement methods are quite useful and could be applied to many fields, such as gamut calculation, and clipping after luminance processing. We also proposed a background adjustment approach cooperates with the proposed saturation enhancement methods to virtually restore the ancient Chinese paintings.

CHAPTER 1 INTRODUCTION 1
1.1 Computer Assistance for Color Vision Deficiency 1
1.2 Color Contrast Enhancement 2
1.3 Thesis Organization 3

CHAPTER 2 CONCEPTS OF COLOR SCIENCE 5
2.1 Light 5
2.2 Human Vision 6
2.3 Color matching 8
2.4 Color Coordinates 10
2.4.1 CIE XYZ and CIE xyY 10
2.4.2 CIE L*u*v* 13
2.4.3 CIE L*a*b* 15
2.5 Display Device Properties 16
2.5.1 Gamma 16
2.5.2 Device Dependent Primaries 16
2.5.3 sRGB 17
CHAPTER 3 COLOR DEFICIENCY 19
3.1 Color Deficient Vision 20
3.2 Computer Simulation of Dichromat vision 24
3.2.1 Brettel’s method 24
3.2.2 Sinthanayothin’s method 28
3.2.3 Inability to Read Color-coded Image 29
3.2.4 Experimental Results 30
3.3 Color Enhancement Assisting Dichromats 32
3.4 Experimental Results 35
3.5 Conclusion 42

CHAPTER 4 SATURATION ENHANCEMENT AND ITS APPLICATIONS 43
4.1 Introduction 43
4.2 Saturation Enhancement in CIE xyY 44
4.2.1 Saturation Enhancement algorithm 47
4.2.2 Experimental Results 50
4.3 Saturation Enhancement in CIE L*u*v* 52
4.3.1 Saturation Enhancement Algorithm in L*u*v* 52
4.3.2 Experimental Results 54
4.4 Virtually Restoring Ancient Chinese Paintings 57
4.4.1. Dominant color 58
4.4.2. Similarity to dominant color 58
4.4.3. Adjust color pixel according to color similarityα 59
4.4.4 Experimental Results 60
4.4.5 Conclusion 63
4.5 Saturation Clipping 64
4.5.1 Saturation Clipping 64
4.5.2 Experimental Results of Saturation Clipping 65
4.6 Conclusion 67

CHAPTER 5 CONCLUSIONS AND FUTURE WORK 69
5.1 Conclusions 69
5.2 Future Work 70

REFERENCES 71

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