
系統識別號 
U00262907201521324400 
論文名稱(中文) 
植基於模糊重力搜尋演算法之影像縮放內插技術 
論文名稱(英文) 
Fuzzy Gravitational Search Algorithm Based Image Zooming Interpolation Scheme 
校院名稱 
成功大學 
系所名稱(中) 
電機工程學系 
系所名稱(英) 
Department of Electrical Engineering 
學年度 
103 
學期 
2 
出版年 
104 
研究生(中文) 
郭建宏 
研究生(英文) 
ChienHung Kuo 
學號 
N27011197 
學位類別 
碩士 
語文別 
英文 
論文頁數 
57頁 
口試委員 
指導教授李祖聖 口試委員孔蕃鉅 口試委員呂虹慶 口試委員郭逸平 口試委員謝銘原

中文關鍵字 
模糊集
重力搜尋演算法
內插法
影像縮放

英文關鍵字 
Fuzzy
GSA
Image Zooming
Interpolation

學科別分類 

中文摘要 
本論文主要在探討如何使用模糊重力搜尋演算法來降低影像縮放時的不協調。影像內插法(Interpolation)區分兩種類型：單一影像與多重影像。前者多使用在圖片修復、重建與局部性放大檢視；而後者大多使用在視覺上，由於可連續取得即時影像，因此可以達到即時縮放效果。在影像縮放處理上，最難部分即是增加或維持影像的銳利度與平滑度，並降低產生的模糊感。
本文所提出的方法是利用傳統的線性(Linear)內插法做修改，使用模糊重力搜尋演算法(Fuzzy GSA)以求得最佳像素補償比例，即使在高倍率縮放時，仍然可以保有清晰的影像。在實驗模擬上，與傳統內插法做比較後，峰值信噪比(PSNR)較高以及影像表現有較佳效果。

英文摘要 
This thesis aims to apply fuzzy gravitation search algorithms to decrease the image zooming inconsistent condition. The image interpolation method distinguishes between the two categories: single frame and multiframe. The latter is often used in visually, due to the continuous access to live images, so a realtime zooming effect can be achieved. The former is mostly used in repair, reconstruction and local pictures to enlarge the view. In the image scaling process, the hardest part is to increase or maintain the sharpness and smoothness of the image and to reduce the blurring.
The proposed method is to modify the traditional linear interpolation method, and make use of the fuzzy gravitational search algorithm in order to achieve optimal compensation rate of pixel. Even if in highmagnification scaling, we still have a clear image. Simulation results demonstrate that the proposed scheme gives a higher peaksignaltonoise ratio (PSNR) and shows a better images results in comparison with traditional method.

論文目次 
Abstract (Chinese) I
Abstract (English) II
Acknowledgment III
Contents IV
List of Figures VI
List of Tables IX
Chapter 1. Introduction
1.1 Motivation 1
1.2 Thesis Organization 5
Chapter 2. Preliminaries
2.1 Introduction 6
2.2 Traditional Interpolation Methods 8
2.3 Description of Gravitational Search Algorithm 12
2.4 Summary 19
Chapter 3. The Fuzzy Gravitational Search Algorithm Interpolation Scheme
3.1 Introduction 20
3.2 Bilinear Interpolation Method 21
3.3 Overview of Problem Formulation 23
3.4 Fuzzy rules and Membership Functions 25
3.5 Fuzzy GSABased Image Zooming Interpolation Scheme 28
3.6 Summary 32
Chapter 4. Experimental Results and Comparison
4.1 Introduction 33
4.2 Test Parameter Settings and Tools 34
4.3 The Test Image of Experimental Results 35
4.4 Comparison with Other Methods 42
4.5 Testing for Region of Interest 46
4.6 The Consumption of Computation time 47
4.7 Summary 49
Chapter 5. Conclusions and Future Study
5.1 Conclusions 50
5.2 Future Study 52
References 53

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