臺灣博碩士論文加值系統

本論文提出一個可以實作於硬體上的影像放大以及強化方法，一般常見的放大以及強化影像方法，都是先透過內插補點的方法將影像放大之後，再針對放大過後的影像做強化，而我們的方法則是可以在放大的同時強化影像。另外，不同於其他相關研究中，較沒有考慮到利用原始影像的資訊直接做不限比例放大或強化，我們則是透過分析原始影像的資訊，去放大影像。在分析原始影像之前，我們會先預先定義出邊緣或是角的種類，接著再針對一個小區塊作分析，判斷這個小區塊的原始影像是否符合我們預先定義的種類，再根據分析的結果選擇要使用內插補點或是外插補點的方式。因此本論文中也會探討小區塊的大小，以及預先定義種類的多寡，對影像放大強化造成的影響。

The thesis proposes an image scaling and enhancement method which is suitable for hardware implementation. Except for very limited image scaling ratios, most image scaling and enhancement methods first scale the image by interpolation, and then enhance the image without considering image content. With analysis of image content, the proposed method scales and enhances the image simultaneously without the above limitation. For such analysis, different pixel patterns of an object edge or corner are pre-defined for a particular window size. For each pattern, proper interpolation/extrapolation scheme is adopted by the proposed method for simultaneous scaling and enhancement. Effects of choosing different window sizes, and associated pixel patterns, on image scaling and enhancement are also examined in detail in this thesis.

表目錄 vi
第一章 簡介 1
1.1 文獻探討 2
1.1.1 適合硬體實作的方法 3
1.1.2 適合軟體實作的方法 4
1.2 影像同時放大及強化流程 6
第二章 基本影像放大方法 9
2.1 影像內插放大概述 9
2.2 基本內插演算法 10
2.2.1 Sinc演算法 11
2.2.2 Nearest Neighbor演算法 13
2.2.3 Linear/Bi-linear演算法 13
2.2.4 Cubic/Bi-cubic演算法 14
2.3 二維度Cubic內插補點演算法 16
第三章 影像放大與強化 17
3.1 基本觀念 17
3.1.1 影像放大後處理之Hi-Boost強化 17
3.1.2 影像放大與強化之內插與外插 22
3.2 內插與外插架構介紹 27
3.3 二維內插外插之影像放大與強化方法介紹 27
3.3.1 判斷2×2區域內邊以及角的處理 28
3.3.1 判斷4×2區域內邊的處理 30
3.3.2 判斷4×4區域內邊的處理 36
第四章 討論 51
4.1 分類的完整性 51
4.2 邊緣的連續性 53
第五章 實驗結果 54
5.1 判斷2×2區域內邊的實驗結果 54
5.2 判斷4×2區域內邊的實驗結果 59
5.3 判斷4×4區域內邊以及角的實驗結果 66
第六章 結論與未來的研究方向 86
參考文獻 87

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