臺灣博碩士論文加值系統

現今的數位顯示技術中，內插演算法是對影像縮放而言，非常重要的技術，尤其是近年來液晶螢幕的尺寸的越來越大。本篇論文提出了一個適應性的內插演算法，是對於近似多項式內插法其鄰近點模糊理論距離分析為適應性。傳統的演算法有模糊或格狀效應的缺點。通常為了改善這些問題設計出很多邊緣偵測的方法，邊緣偵測是高複雜度而且高成本的設計架構。依據研究結果顯示，提出的方法影像銳利度也比其他演算法高,本論文提出了一個不但能增強邊緣而且有較好影像品質的演算法。在PSNR值上高出雙立方內插法0.4dB。並以Altera CycloneII FPGA來完成硬體的實現，將SVGA（800×600）的視訊格式即時轉換至WXGA（1280×768）(60畫面/每秒)的全彩畫面格式，顯示在液晶面板上。

With the increasing use of digital monitor technique, requirements for image interpolation have become more critical. This thesis presents an adaptive image interpolation algorithm based on the slope analysis of adjacent pixel gray values for an approximate polynomial method. Conventional interpolation methods have several drawbacks, such as blurring or blocky effects. Many edge detect methods have been widely used to avoid these problems but are notorious for high complexity and cost. Simulation results show that PSNR value of proposed algorithm is higher than bicubic algorithm around 0.4dB. Besides, sharpness of proposed algorithm is also much higher than that of other ones. In this thesis, an algorithm which not only enhances edge but also gets better image quality algorithm is proposed. The FPGA implementation of the proposed video scaling algorithm is from SVGA to WXGA on the TFT-LCD plane at the real time video rate of the 60 frames/sec.

謝誌 i
ABSTRACT ii
中文摘要 iii
TABLE OF CONTENT iv
LIST OF FIGURES vi
LIST OF TABLES viii
CHAPTER 1 1
INTRODUCTION 1
1.1 Motivation 1
1.2 Thesis Review 1
1.3 Content-Based Interpolation 2
1.4 Purpose of Research 3
CHAPTER 2 4
CONECT OF EXITING INTERPOLATION METHODS 4
2.1 Overview 4
2.2 Reconstruction System 4
2.3 Conventional Interpolation 5
2.3.1 Nearest Neighbor 5
2.3.2 Bilinear Interpolation 6
2.3.3 Cubic Convolution 9
2.3.4 Polynomial Interpolatios84 9
2.3.5 Win-scale Interpolation algorithm 11
CHAPTER 3 14
ADAPTIVE IMAGE INTERPOLATION 14
3.1 Adaptive Content-based Interpolation 14
3.1.1 Adaptive Interpolation Algorithm For Real-time Image Resizing 14
3.1.2 Adaptive Pseudo-median Interpolation 16
3.1.3 Adaptive Image Interpolation Based On Local Gradient Features………………………………………………………... 17
3.2 Image Processing In Edge Region 20
3.2.1 Concept 21
3.2.2 Edge Enhancement 21
3.2.3 Gradient Edge Enhancement 22
3.2.4 Laplacian Edge Enhancement 24
CHAPTER 4 28
THE PROPOSED IMAGE SCALING UP ALGORITHM 28
4.1 Overview 28
4.2 The Second Order Polynomial Method 29
4.3 Fuzzy Adaptive Edge Enhanced System 33
CHAPTER 5 37
THE PROPOSED IMAGE SCALING UP ALGORITHM EXPERIMENTAL RESULTS37
5.1 Experimental Results37
5.2Architecture of Scan Converter46
CHAPTER 6 50
CONCLUSIONS50
REFERENCES51

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