在這篇論文，我們提出一個新穎彩度抽樣模型針對RGB全彩影像使用提取的彩色濾波陣
列資訊。彩色濾波陣列資訊可以被提取，首先藉由相機模組辨識方法辨識出全彩影像的相機
模組，然後將辨識的相機模組當作查詢金鑰從對照表去提取出彩色濾波陣列結構和模組資
訊。接著，使用提取的彩色濾波陣列資訊，我們提出一個彩色濾波陣列區塊失真最小化彩度
抽樣架構，叫作CFA-BMCS。更進一步，針對CFA-BMCS，我們提出一個幾何搜尋演算法，
針對2x2 UV 區塊去決定最好的彩度抽樣(U, V)值。在知名的Dresden影像測試集，根據83
張RGB全彩影像，實驗結果展示在目前的高效率視頻編碼軟體，版本HM-16.17，在還原的
影像上，和六個存在的彩度抽樣方法比較，提出的CFA-BMCS方法有可觀的品質和品質位
元率權衡優勢。除此之外，我們修改提出的CFA-BMCS方法來解決輸入影像為Bayer彩度濾
波陣列影像的情況。實驗結果展示修改的CFA-BMCS方法在還原的Bayer彩度濾波陣列影像
上，優於2個最新的方法。

In this thesis, we propose a new chroma subsampling model for the RGB full-color image I^RGB using the extracted color filter array (CFA) information of I^RGB. The CFA information can be extracted by first applying the camera model identification method to recognize the camera model used to capture I^RGB, and then taking the recognized camera model as the query key to extract the CFA structure and module information from the lookup table built up in advance. Next, using the extracted CFA information, we propose a CFA block-distortion minimization-based chroma subsampling scheme, called CFA-BMCS. Further, we propose a geometry-based search algorithm to determine the best subsampled chroma (U, V)-pair for each 2x2 UV block for CFA-BMCS. Based on the 83 RGB full-color images in the well-known Dresden set, the experimental results demonstrated that in the current High Efficiency Video Coding (HEVC) reference software HM-16.17, the proposed CFA-BMCS method has substantial quality and quality-bitrate tradeoff merits of the reconstructed images when compared with the six existing chroma subsampling methods. In addition, we modify the proposed CFA-BMCS method to solve the chroma subsampling problem when the input image is the Bayer CFA image. The experimental results showed that the quality of the reconstructed Bayer CFA image by the modified CFA-BMCS method is clearly superior to the two state-of-the-art methods.

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