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研究生: 張嘉裕
Jia-Yu Chang
論文名稱: 無週期半色調及多色調延伸技術之研究
Aperiodic Digital Halftoning and Its Multitoning Extension
指導教授: 郭景明
Jing-Ming Guo
口試委員: 賴坤財
Kuen-Tsair Lay 
陳鴻興
Hung-Shing Chen
楊士萱
Shih-Hsuan Yang
范育成
Yu-Cheng Fan
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 287
中文關鍵詞: 數位半色調技術數位多色調技術統計式查表法點擴散法錯誤擴散法
外文關鍵詞: halftoning, multitoning, look-up table, dot diffusion, error diffusion
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  • 本論文中提出兩種改良式之數位半色調技術與一種改良式之數位多色調技術以供硬體輸出設備之使用。數位半色調技術主要功能是將連續色階影像轉換至有限色階影像,並且以有限色階表現連續色階之結果。由於色階數量的降低,將會造成轉換影像有所失真,因此如何降低此失真情況以產生良好的影像品質,為數位半色調技術的研究目標之一。此外,現今影像解析度越來越高,人們對於印表機處理速度之要求,數位半色調技術必須快速地轉換影像以供硬體輸出設備之使用,因此數位半色調技術的處理效能也將納入評估的項目。
    本論文前半部分基於提高影像品質與處理效能提出兩種數位半色調技術。有鑑於統計式查表法之高效率處理之特性,本論文提出的第一個方法為多查詢表之查表法。統計式查表法雖然在點分佈上能有接近直接二元搜尋法的特性,不過透由自相關評估工具就可發現其差異,在本方法中數個查詢表將依不同特徵分類並適應不同的影像內容以提供更佳的點分佈特性。在實驗結果中驗證此方法與直接二元搜尋在點分佈上具有高相似性。第二個方法為相依於影像內容之點擴散法,其中點擴散法具有平行處理之特性,但週期性圖樣帶來的負面效應,造成影像品質的降低,因此本方法提出有效抵抗週期性圖樣之改良式之點擴散法藉此提升影像品質,並且同時保有點擴散法的平行處理之特性。在實驗結果中驗證此方法在具平行處理特性之方法中能提供最佳的影像品質,並且在影像結果中不具週期性圖樣。
    本論文後半部分以提升影像品質為主要目標,提出一種改良式之數位多色調技術,該技術為數位半色調技術之延伸技術,其特色為具有較多的輸出色階以降低轉換時的失真情況。雖然數位多色調技術能夠提供更高的影像品質,但是帶狀效應會造成負面的影響,因此本論文提出色調替代之錯誤擴散法以抵抗帶狀效應。在實驗結果中驗證此方法為一個有效率的演算法,並能提供高影像品質多色調影像,實驗結果可看出帶狀效應明顯被消除,影像品質遠較前人所提方法來得好。


    In this thesis, three techniques, including two improved digital halftoning algorithms and one digital multitoning algorithm, are proposed to convert images for output devices. Digital halftoning is a technique for converting continuous-tone images into limited-tone images. The distortion between an original image and the converted image is inevitable, since the number of the corresponding output levels is less than the continuous-tone. Thus, the main object of the halftoning is to reduce the distortion induced from this transformation. Nowadays, the processing performance of the halftoning has become a critical issue as the image resolution is increasing. Another key element of this thesis is to effectively boost the processing efficiency.
    The first proposed method is the Multiple Look-Up Table (MLUT) which is based on the look-up table halftoning, and is an effective technique for yielding satfactory image quality. According to the experiment results, the dot distribution generated by the proposed method can approximate to the well-known direct binary search halftoning which can achieve the best image quality so far, and thus it can be a very competitive candidate in coping printing industry. The second proposed method is the Content-Dependent Dot Diffusion (CDDD) which is based on Dot Diffusion (DD). The proposed CDDD can provide better image quality and a near aperiodic characteristic simultaneously comparing to the former parallel methods.
    The multitoning is a technique which extends the halftoning by adopting more than two quantification levels for reducing the distortion between an original image and the converted image. Yet, the banding effect disturbs the visual perception, and thus degrades the image quality. To improve the image quality by removing the banding effect, the third method termed Tone-Replacement Error Diffusion multitoning (M-TRED), is proposed. According to the experimental results, the proposed method can provide excellent tone-similarity and dot-distribution simultaneously comparing to the former banding-free methods in the literature.

    中文摘要 Abstract 誌謝 目錄 圖表索引 第一章 緒論 1.1研究背景與動機 1.2研究目的 1.3論文架構 第二章 數位半色調技術文獻探討 2.1區塊取代法(Block Replacement, BR) 2.2限制平均法(Constrained Average, CA) 2.3有序抖動法(Ordered Dithering, OD) 2.4藍雜訊遮罩有序抖動法(Blue-Noise Mash Ordered Dithering, BNMOD) 2.5錯誤擴散法(Error Dissusion, ED) 2.6點擴散法(Dot Diffuison, DD) 2.7網格擴散法(Grid Diffusion, GD) 2.8 直接二元搜尋法(Direct Binary Search, DBS) 2.9統計式查表法(Statistical Look Up Table, SLUT) 2.10 基於直接二元搜尋法設計藍雜訊遮罩有序抖動法 第三章 數位多色調技術文獻探討 3.1 多色調有序抖動法(Multitoning Ordered Dithering, M-OD) 3.2 多色調錯誤擴散法(Multitoning Error Diffusion, M-ED) 3.3 多色調直接二元搜尋法(Multitoning Direct Binary Search, M-DBS) 3.4 使用過度調變之多色調有序抖動法(M-OD with Over-Modulation) 3.5 多色調多尺度錯誤擴散法(Multitoning Multi-Scale Error Diffusion) 3.6 多色調藍雜訊抖動法(Multitoning Blue-Noise Dithering, M-BND) 第四章 基礎技術介紹 4.1 方向場(orientation field) 4.2 快速標準差計算(Quick Standard Deviation Evaluation, QSDE) 4.3 最佳化演算法(optimization algorithm) 4.4 峰值訊噪比(Peak Signal-to-Noise Ratio, PSNR) 4.5 自相關(AutoCorrelation, AC) 4.6 放射狀平均功率頻譜密度(Radial Averaged Power Spectral Density) 第五章 多查詢表之查表法 5.1 查詢表特徵 5.2 訓練階段 5.3 重建階段 5.4 實驗結果 5.5 小結 第六章 無週期性圖樣之點擴散法 6.1 類別矩陣轉換 6.2 類別順序層安排 6.3 影像內容分類 6.4 類別矩陣與擴散矩陣最佳化 6.5 實驗結果 6.6 小結 第七章 無帶狀效應之數位多色調技術 7.1 多色調色調替代之錯誤擴散法 7.2 最佳化錯誤濾波器 7.3 實驗結果 7.4 小結 第八章 結論與未來展望 參考文獻 作者簡介

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