臺灣博碩士論文加值系統

在影像編輯過程中很容易產生各種影像瑕疵(Artifacts)，會因為影像編輯的過程不嚴謹，像是編碼精度(Bit-Depth)不足而使的色彩梯度(Color gradient)在經過量化後進而產生假輪廓(false contouring) ，並且廠商通常也會在影像後製的時候使用影像濾鏡(Filter)進一步破壞顏色訊息，同時各個編碼也會造成損失，像是線上平台Youtube上傳的影片、軟體Adobe effect的編碼輸出，都會使用h.264、MPEG等有損編碼(lossy compression)，而這些影像都會有各種影像瑕疵。因此提出一個基於高精度(High Bit-Depth)與影像增強處理的濾鏡算法，能夠適用於高畫質的影像處理，針對去色帶、去除假輪廓、去除雜訊的自適應處理方式，並獲得一個良好泛用的結果。

Incautious procedure of image processing could easily cause kinds of Artifacts. For example, insufficient encoding bit depth results in the false contouring when color gradient is quantified.

Also, many video manufacturers are used to apply video filter later, which will cause the loss of color bit; meanwhile, different lossy compression(one of the common data encoding methods in information technology) methods, like H.264, MPEG, etc, are widely used by online streaming uploaded video platform like youtube, or software like Adobe After Effect. However, all of them are inevitably containing artifacts due to the lossy compression.

To obtain the better image quality, therefore, a filter algorithm based on high bit depth and image enhanced processing framework has been proposed for high quality image processing results.

This algorithm is also an adaptive filter which can automatically decide whether debanding, decontouring, denoise should be adopted resulting in better common results.

中文摘要 i
Abstract ii
誌 謝 iii
目 錄 iv
圖索引 v

第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究問題 2
第三節 研究目的 3
第四節 論文架構 3

第二章 文獻探討 5
第一節 圖像噪點(Image Noise) 5
第二節 動態噪點(Motion Noise) 6
第三節 測量品質 7
第四節 Butteraugli 7
第五節 去噪方法 8
第六節 邊緣檢測(Edge detection) 10
第七節 圖像增強(Image Enhancement) 16
第八節 圖像色帶(Color banding) 16

第三章 算法架構與實驗 21
第一節 算法開發目的 21
第二節 算法與流程圖 22
第三節 去噪過程的實驗(Denoise) 29
第四節 去色帶與去除假輪廓過程的實驗(Debanding and Decontouring)35
第五節 實驗結果與分析 41

第四章 結論與未來展望 46
第一節 結論與貢獻 46
第二節 研究限制與未來展望 47

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