臺灣博碩士論文加值系統

黑暗通道優先是根據戶外沒有霧的影像使用大數據進行的統計資訊。並且黑暗通道優先已經在對單張影像進行去除霧方面成功。由於它的成功，本論文主要探討基於黑暗通道優先上的彩色影像增強演算法。這些演算法包含影像去除霧方法、陰影/背光影像增強方法和海底影像增強方法。許多數值範例和實驗結果可以證明所提出的影像增強方法比傳統的方法更具有彈性。

The dark channel prior (DCP) is a big-data statistics of outdoor haze-free color images. The DCP has been successfully used in the single image haze removal. Due to its success, the purpose of this paper is to develop some color enhancement algorithms based on DCP. These algorithms include a backlighting image enhancement method, a generalized single haze removal method, and an underwater image enhancement method. Several numerical examples and experiments are shown to demonstrate that the proposed image enhancement methods provide higher flexibility than the conventional methods in the literature.

中文摘要 I
英文摘要 II
致謝 III
目錄 IV
表目錄 VI
圖目錄 VII
壹、緒論 1
1.1 簡介 1
1.2 論文架構 2
貳、暗通道優先原理簡介 3
2.1 黑暗通道優先（Dark Channel Prior）的定義及計算 3
2.2 結果與結論 9
参、基於暗通道優先的影像除霧方法 10
3.1 簡介 10
3.2 霧的模型 11
3.3 除霧方法 12
3.3.1 流程圖 12
3.3.2 估算大氣光A 13
3.3.3 傳輸矩陣t(x) 13
3.3.4 精緻化傳輸矩陣 14
3.3.5 回復場景影像J 15
3.4 區域補丁(Ω) 17
3.5 實驗結果 21
3.6 結果與討論 24
肆、基於暗通道優先的陰暗/背光影像增強方法 25
4.1 簡介 25
4.2 背光影像的模型 26
4.3 使用暗通道優先對陰暗/背光影像增強方法 27
4.3.1 使用暗通道優先對陰暗/背光影像增強流程圖 27
4.3.2 實做方法 28
4.4 實驗結果 33
4.5 結果與討論 43
伍、基於暗通道優先的海底影像增強方法 44
5.1 簡介 44
5.2 使用暗通道優先的海底影像增強 45
5.2.1 使用暗通道優先的海底影像增強方法的流程圖 46
5.2.2 實做方法 47
5.3 實驗結果 54
5.4 結果與討論 58
陸、結論與未來展望 59
6.1 結論 59
6.2 未來展望 60
柒、參考文獻 61

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