臺灣博碩士論文加值系統

為了改善對於低照度影像以及照度不均影像，本論文各提出一個演算法對於低照度影像和照度不均影像做光線照度明暗的處理，之後再使用一個『基於邊緣檢測之適應性模糊影像增強』的方法做影像加強使得影像對比更加強。最後實驗結果證明，我們所提出的方法針對低照度影像和照度不均影像可以有較佳的增強效果並且也可以保留更多的細膩度。

In this thesis, Fuzzy image enhancement algorithms for low illumination image and uneven illumination image are proposed. The global brightness enhancement and the fuzzy contrast enhancement are performed for low illumination image. The uneven illumination enhancement and the fuzzy contrast enhancement are performed for uneven illumination image. The experimental results show that low illumination images and uneven illumination images can be effectively enhanced.

ACKNOWLEDGMENTS i
ABSTRACT ii
中文摘要 iii
LIST OF FIGURES vii
LIST OF TABLES xiii
CHAPTER 1 INTRODUCTION 1
1.1 Image Enhancement 1
1.2 Fuzzy image enhancement 1
1.3 Image enhancement for low illumination image and uneven illumination image 2
CHAPTER 2 OVERVIEW OF FUZZY IMAGE ENHANCEMENT 4
2.1 Introduction 4
2.1.1 Definition of Image in Fuzzy Theory 4
2.1.2 Fuzzy Domain and Membership Function 5
2.1.3 Contrast Intensification 6
2.1.4 The Inverse Transformation 7
2.1.5 The Drawbacks of Pal and King’s Algorithm 7
2.2.1 Normalization 8
2.2.2 A new membership function 8
2.2.3 A new contrast intensification operator 10
2.2.4 The inverse function 11
2.2.5 Transform the original RGB color modol to HIS color model 12
2.3 Experimental results 14
CHAPTER 3
IMAGE ENHANCEMENT FOR LOW ILLUMINATION IMAGE 28
3.1 Introduction 28
3.2 Proposed algorithm for low illumination gray image 30
3.2.1 Global brightness enhancement 31
3.2.2 The new mapping function 32
3.3 Proposed algorithm for low illumination color image39
CHAPTER4
IMAGE ENHANCEMENT FOR UNEVEN ILLUMINATION IMAGE 46
4.1 Introduction 46
4.2 Proposed algorithm for uneven illumination gray image 48
4.2.1 Uneven illumination enhancement 49
4.2.2 Mean filter 50
4.2.3 Uneven illumination enhancement 51
4.3 Proposed algorithm for uneven illumination color image 60
CONCLUSION 68
REFERENCES 69

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