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研究生: 蔡育文
Yu-Wen Tsai
論文名稱: 一種植基於區域視窗選擇的高效能影像增強演算法
A High-Performance Contrast Enhancement Algorithm Based on Regional Window Selection
指導教授: 阮聖彰
Shanq-Jang Ruan
口試委員: 廖弘源
Liao, Mark
李佩君
Pei-Jun, Lee
鍾國亮
Kuo-Liang Chung
許孟超
Mon-Chau Shie
學位類別: 碩士
Master
系所名稱: 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 66
中文關鍵詞: 對比增強直方圖等化二維直方圖累積式直方圖
外文關鍵詞: Contrast enhancement, histogram equalization, 2-D histogram, integral histogram
相關次數: 點閱:282下載:8
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在惡劣的環境影響下所取得的影像往往因為影像對比偏低使得影像細節不容易察覺,這將不利於後續相關影像處理技術的應用。一種基於二維直方圖的影像對比增強演算法可以有效的改善影像對比以及保留影像的平均亮度。由於二維直方圖參考了像素與像素間的資訊,在建立直方圖的計算上需要耗費了相當大的時間。本論文提出了一種累積式二維直方圖的建立方法,並且考慮了影像各個區塊內的影像細節及灰階值間的變異,動態的決定每個區塊內建立二維直方圖所需要的視窗大小。經過本論文的方法,二維直方圖的時間複雜度有效改善為線性時間,並且對於影像對比增強後的影像,在凸顯細節以及亮度的保留在實驗數據上均顯著地提升。


Contrast enhancement is used to improve the quality of low contrast images that are usually captured in poor environments. Considering contextual and variational characterization, a 2-D histogram based contrast enhancement algorithm was proposed. To balance contrast enhancement and brightness preservation, the window size of a 2-D histogram based contrast enhancement should be larger or smaller by considering the details of different parts in the image. Furthermore, its computation time is also an important issue for different real-time applications. In this paper, we propose a O(1) dynamic range 2-D histogram construction algorithm to effectively solve these problems. The proposed algorithm divides the image into various blocks and gives different neighbourhood size, which depends on the variation of intensity and the image details of each block. Compared to the prior work, the number of pixels are dynamically constructed in the 2-D histogram, while the integral histogram is achieved to be O(1) complexity. Experimental results show that the proposed algorithm generates high contrast images and preserves the local brightness in constant time.

Table of Contents Recommendation Form Committee Form Chinese Abstract English Abstract Acknowledgements Table of Contents List of Tables List of Figures Table of Algorithms 1 Introduction 1.1 Introduction to Contrast Enhancement 1.2 Histogram-Based Contrast Enhancement Approaches 1.3 Organization of This Thesis 2 Related Works 2.1 Conventional Histogram Equalization 2.2 Brightness Preserving Bi-Histogram Equalization 2.3 Dynamic Histogram Equalization 2.4 Contextual and Variational Contrast Enhancement 2.5 Motivations 3 Proposed method 3.1 Dynamic Neighbourhood Size Selection 3.2 2-D Histogram Generation Using Integral Histogram 3.3 Enhanced Process 4 Experimental Result 4.1 Qualitative Assessment 4.2 Quantitative Assessment 4.3 Computational Complexity 5 Conclusions References Appendix Copyright Form

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[18] Retrieved on June 2013 from the World Wide Web [Online]. Avail-able: http://sipi.usc.edu/database/
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