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研究生:陳明仁
研究生(外文):Ming-Ren Chen
論文名稱:權重MinMax彩色影像量化法之改進
論文名稱(外文):A Modification of Weighted MinMax Algorithm in Color Image Quantization
指導教授:薛元澤薛元澤引用關係
指導教授(外文):Yuang-Cheh Hsueh
學位類別:碩士
校院名稱:國立交通大學
系所名稱:資訊科學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:71
中文關鍵詞:量化彩色影像量化分群法MinMax 演算法
外文關鍵詞:QuantizationColor Image QuantizationClusteringMinMax Algorithm
相關次數:
  • 被引用被引用:2
  • 點閱點閱:360
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
就影像處理而言, 彩色影像量化是一個產生高品質壓縮影像非常有用的技巧。在這篇論文中, 我們提出一個新的彩色影像量化技巧, 改良自權重MinMax 演算法。我們的方法是MinMax 和K-Means 這兩種演算法的混合並基於權重的histogram而產生的新的演算法。我們的演算法並不嚐試去尋求量化問題的最佳解答, 取而代之的是去尋求每一個群最佳的切割方式, 最主要的觀念是基於將每一個群內部的最大群距最小化。不同於權重MinMax演算法的是我們的方法具有較佳的效率, 而且經過量化處理之後的影像品質也非常好。同時我們提出的改良式演算法亦具有容易實作的優點。
For image processing, the color image quantization is a useful technique to produce high quality compression image. In this thesis, we present a new color image quantization technique that modifies the weighted MinMax algorithm. It is a hybrid method of MinMax and K-Means algorithms and based on weighted histogram. Instead of trying to solve an optimization problem, our algorithm is aiming to get the best-spread representation of the cluster in the color space. The main concept is based on minimizing the maximum intercluster distance. Unlike weighted MinMax algorithm, our method is more efficient and the quality of quantized image is good. In the mean time it is easy to implement also.
CONTENTS
ABSTRACT(CHINESE) i
ABSTRACT(ENGLISH) ii
ACKNOWLEDGEMENTS iii
CONTENTS iv
LIST OF FIGURES vii
LIST OF TABLES xi
1. Introduction 1
1.1 Motivation 1
1.2 Introduction to Quantization 3
1.3 Organization of This Thesis 4
2. Overview of Color Image Quantization 6
2.1 Color Fundamentals 6
2.1.1 The RGB Color Space 6
2.1.2 The Luminance Considered 8
2.2 Original and Quantized Images 9
2.3 3-D Histogram of The Color Image 10
2.4 Sampling (prequantization) The Original Image for
Color Statistics 11
2.5 Color Palette Generation 13
2.6 Pixel Mapping 15
2.7 Color Distance and Quantization Error Measured 16
2.8 Dithering 17
2.8.1 Ordered Dithering 18
2.8.2 Error Diffusion 19
3. Survey of Related Works 21
3.1 Uniform Quantization 21
3.1.1 Fixed 256-Color Palette 21
3.1.2 Discussion 23
3.2 Non-Uniform Quantization 24
3.2.1 Median-Cut Algorithm 24
3.2.2 Mean-Split Algorithm 26
3.2.3 K-Means algorithm 28
3.2.4 Discussion 30
4. The Weighted MinMax Algorithm and Its Modification 33
4.1 The Original Weighted MinMax Algorithm 33
4.1.1 Distance Function 33
4.1.2 Luminance Consideration and Spatial Activity Weighting 34
4.1.3 Pseudocode for Weighted MinMax Algorithm 36
4.2 Modification of Weighted MinMax Algorithm 38
4.2.1 The Idea of modify Weighted MinMax Algorithm 38
4.2.2 The 3-D Histogram Generation 40
4.2.3 The Modified Algorithm Details 41
4.2.3.1 Reducing the Color Space for Representative Color
Selection 41
4.2.3.2 Fast Reassign Color to New Cluster 41
4.2.3.3 Representative Colors Selection 43
4.2.4 Destined Pixel Mapping 46
4.2.5 Dithering 47
4.3 Experimental Results 48
4.4 Discussion 65
5. Conclusions and Future Work 67
5.1 Conclusions 67
5.2 Future work 68
References 69
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