臺灣博碩士論文加值系統

在這篇論文擬提出一個以適應性量化器為基礎，並結合離散小波轉換技術的影像壓縮系統，未來將可應用於數位相機及電子視訊等領域。整個論文包含了量化器的選擇、量化區間的大小影響、及小波轉換的應用之可行性評估。離散小波轉換在影像壓縮方面已應用非常廣泛，因為它有著較高的壓縮率且較好的容錯率，但是在量化器上，採用唯一的方式，有著一定的點，較不能針對不同的影像，產生一樣的良率，例如ㄧ般數位影像及人工數位影像，但是藉由適應性量化器，可以解決這方面的問題，而且它也保留了無失真及可失真的兩種模式，針對不同的壓縮率，它皆可提供不錯的方案。

In this paper, we propose an image compression system integrating Discrete Wavelet Transform (DWT) and adaptive quantizer design. The design considers the selection of quantization tables, the appropriate length for quantization intervals, and the DWT sub-bands quantization applied to. The proposed system can be efficiently employed in a variety of applications like digital cameras and computer vision. DWT has been applied in image compression for years since it provides considerable compression rate and supports multi-resolution representation. However, when the DWT coefficients are quantized by a fix quantizer, the image quality is a case-by-case parameter. Images with different characteristics result in different system performance values. With an adaptive quantizer, the users can select lossy or lossless mode according to their own requirements for image quality. Furthermore, the system performance becomes a stable parameter for the compression system.

第一章 簡介…………………………………………..1
1.1 研究背景及目的………………………………….1
1.2 研就動機.………………………………………..2
1.3 文章架構….……………………………………..2
第二章 文獻探討………………………………......4
2.1 相關背景與分類……………………………..…4
2.2 專關專業知識與文獻回顧.……………………..8
第三章 研究方法……………………………………13
3.1 編碼端流程………………………………………13
3.1.1 傳統模式……………………………………..13
3.1.2 適應性模式…………………………………..15
3.2 解碼端流程………………………………………18
3.2.1 傳統模式………………………………………18
3.2.2 適應性模式……………………………………19
3.3 判斷法則…………………………………………20
第四章 實驗結果與分析……………………………21
4.1 實驗結果…………………………………………24
4.2 效能分析…………………………………………26
第五章 結論與未來研究目標………………………28
5.1 結論………………………………………………28
5.2 未來研究方向與目標……………………………29

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