為了節省製造成本，多數的數位攝影機採用了單一感測器的技術搭配色彩濾波陣列來捕捉真實世界的場景。由於在每一個像素位置上僅有紅、綠、藍三者其中之一的顏色感測器，因此這類的視訊影片常被稱為馬賽克視訊。為了節省儲存空間與增進傳輸效能，如何達到良好的品質與容量權衡對馬賽克視訊壓縮是十分重要的。在本篇論文中，基於數學最佳化的技巧，我們提出了一個新穎的彩度抽樣策略，而其可適用於在 H.264/AVC 與 HEVC 中壓縮任意色彩濾波陣列樣式的馬賽克視訊。針對每個將被抽樣成 4:2:0 格式的 2 × 2YUV 區塊，本論文透過最小化原始的馬賽克區塊和抽樣後 YUV 區塊轉換回去的馬賽克區塊彼此之間的失真，來產生出更恰當的抽樣 U 、 V 彩度值。 透過本篇論文的數學最佳化策略，抽樣後的 U 、 V 值可以同時將原始的馬賽克區塊上 R 、 G 、 B 像素對重建馬賽克區塊的重要性皆納入考量。

實驗結果顯示，在利用 H.264/AVC 和 HEVC 視訊壓縮標準來壓縮任意色彩濾波陣列樣式的馬賽克視訊時，本論文所提出的彩度抽樣策略不論是和目前最新的方法─陳等人及楊等人的方法，或是和三個傳統常用的抽樣策略相比，在相近的時間需求下，都有著最佳的品質與容量權衡。

To save the manufacturing cost, most color digital video cameras employ a single-sensor technology with a red-green-blue (RGB) color filter array (CFA) to capture the real-world scenes. Due to only one primary color measured at each pixel location, the captured videos are usually referred to as the mosaic videos. For the purposes of economical storage and transmission, it is very important to achieve a good trade-off between the quality and bitrate when compressing mosaic videos with different RGB-CFA structures. In this paper, based on mathematical optimization technique, a novel chroma subsampling strategy is presented for compressing mosaic videos with arbitrary RGB-CFA structures in H.264/AVC and HEVC. For each 2 × 2 YUV block to be subsampled with 4:2:0 format, the proposed strategy determines the proper sampled U and V components by minimizing, prior to compression, the quality distortion between the original co-located mosaic block and the mosaic block conversed from the current subsampled YUV block. Through the mathematical optimization formulated in the proposed strategy, the significance of the sampled U and V components for reconstructing R, G, and B pixels can be simultaneously taken into consideration. Experimental results demonstrate that the proposed chroma subsampling strategy has the best quality and bitrate trade-off at a similar execution-time requirement for compressing mosaic videos with arbitrary RGB-CFA structures in H.264/AVC and HEVC when compared with the state-of-the-art ones by Chen et al. and Yang et al. as well as the three commonly used ones.

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