過去針對彩色濾波器陣列去馬賽克的方法可區分為兩類：針對單一彩色濾波
器陣列樣式所設計之去馬賽克方法，與適用於任意彩色濾波器陣列樣式的通用型
去馬賽克方法。前者雖然能夠提供較佳的去馬賽克品質，但卻只適用於特定樣式
的彩色濾波陣列；後者雖然可以適用於任意樣式的彩色濾波陣列，但其去馬賽克
品質則受到彩色濾波器陣列不同的變化，時而造成嚴重彩虹邊效應。在本篇論文
中，我們則提出一個可適用於任意樣式之彩色濾波陣列的高品質去馬賽克方法。
過去Yang 等人曾提出一個適用於任意樣式彩色濾波陣列的去馬賽克方法，但其
方法對於各個像素在去馬賽克過程中所需之邊的方向判斷上，將會產生不一致性
的問題，因而導致去馬賽克後出現嚴重彩虹邊效應。在我們所提出的方法中，特
別處理了有關邊方向的一致性問題，來使得彩虹邊效應能夠有效地被解決與改
善，其中主要提出兩大方面之設計：第一是在測邊方法上，藉由考慮相鄰像素在
範圍距離內計算方向上色差值變化，以達到在任意樣式之彩色濾波陣列影像上進
行測邊；第二則是運用傅立葉轉換概念，在任意樣式之彩色濾波陣列影像上，針
對馬賽克顏色值計算對應特定頻譜而得到的亮度濾波器，進一步可結合不同測邊
器，來得到各個像素在不同方向上的梯度值，透過像素不同方向的梯度值，將可
提供更精確之權值來執行去馬賽克內插運算，因而得到更佳之影像品質。實驗結
果顯示在與過去所提出之適用於任意樣式彩色濾波陣列之去馬賽克方法相比，我
們所提出之去馬賽克方法共包含以下優勢：可適用於任意樣式與任意色彩之彩色
濾波器陣列影像、提升去去馬賽克後之影像品質和消除嚴重之彩虹邊效應、具有
較高的CPSNR品質與較小的S-CIELAB誤差。

To save cost, nowadays most digital cameras equip with a single sensor covered
with a specific color filter array (CFA) and each pixel in the captured CFA image is composed of only one color. Universal demosaicing is the process to reconstruct the full-RGB (red-green-blue) color image through an input arbitrary CFA image. In this thesis, we propose a novel quality-efficient universal demosaicing method which exploits both the edge information and the color correlation during demosaicing and can work for arbitrary RGB and non-RGB CFA images. In the proposed method, two main contributions are made and they are (1) an edge-directed color difference based interpolation is designed to specially demosaic the edge regions which usually appear severe artifacts by using the existing universal demosaicing methods and (2) a Fourier transform-based technique combined with the Sobel edge detection is developed to derive the masks of extracting gradient information from arbitrary CFA images so as to provide proper weights to the proposed edge-directed interpolation,
leading to better quality of the demosaiced image. Based on the 24 typical testing images from Kodak collection, experimental results showed that the proposed universal demosaicing method possesses the quality advantage in terms of average color peak signal-to-noise ratio (CPSNR) and S-CIELAB and demonstrates less color artifacts in terms of visual perception when compared with the three state-of-the-art universal demosaicing methods and some existing demosaicing methods designed for non-RGB CFA images.

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