絕大多數商用數位彩色相機使用最廣泛的彩色濾色陣列（CFA）是拜爾模組，其拍攝下來的影像我們稱之為拜爾彩色濾色陣列影像。每個像素中僅有一個色彩值，而紅色、綠色和藍色分別涵蓋的比率為25%、50%和25%。一般HEVC壓縮通常對RGB全採影像做彩度抽樣，而我們取而代之改用拜爾濾色影像做4:2:2或4:2:0彩度抽樣。在解碼端，4:2:2或4:2:0抽樣的彩度影像將使用內插法上抽樣成4:4:4的全彩度影像，再轉成拜爾濾色影像。最後，透過解馬賽克重建出RGB全採影像。根據區塊失真最小化原則，本論文提出在高效率視訊編碼針對拜爾彩色濾色陣列影像之有效梯度下降彩度抽樣（GDCS）方法，與現存的彩度抽樣方法所獲得的重建影像比較，實驗結果顯示我們的方法具有更好的品質與品質位元率權衡優勢。

The most widely used color filter array (CFA) pattern in commercial digital color cameras is the Bayer pattern, and the captured image is called the Bayer CFA image, in which each pixel contains only one color value and each image consists of 25% red, 50% green, and 25% blue color values. Instead of doing chroma sabsampling of RGB full-color image, we do chroma 4:2:2 or 4:2:0 subsampling of the Bayer CFA images prior to compression. On decoder side, 4:2:2 or 4:2:0 subsampled chroma image will be upsampled to 4:4:4 full chroma image using interpolation. After converting to Bayer CFA image, the RGB full-color image will be restructured through demosaicking. According to the block-distortion minimization principle, in this thesis, we propose an effective gradient descent-based chroma subsampling (GDCS) method for Bayer CFA images. Based on the test Bayer CFA images collected from the Kodak and IMAX datasets, experimental results demonstrated that in High Efficiency Video Coding (HEVC), our GDCS method has better quality and qualitybitrate tradeoff performance of the reconstructed images when compared with the existing chroma subsampling methods.

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