最新一代視訊編碼標準為高效率視頻編碼（HEVC），比先前的視訊編碼
標準有更好的編碼效率，HEVC的編碼單元採用了四分樹的編碼架構增加編
碼效能。
　畫面內預測當中，為了使預測更準確，使用了３５個模式來進行預測，同時也大幅增加編碼複雜度。本篇論文提出一個應用於畫面內編碼的CU深度快速決策演算法，擷取畫面資訊以及空間上的相關性作為特徵，包含變異數、低頻交流值以及鄰近編碼單元深度資訊，並利用SVM判斷當前編碼單元是否該往下進行切割。接著我們利用RDO(Rate-Distortion Optimization)程序中各候選模式的SATD成本參數與該預測單元最小SATD成本參數比較，若其大於閥值，就刪除剩餘候選模式，藉此減少候選模式個數以達節省時間的效果。第四章我們會介紹螢幕內容編碼，隨著近年來手機、雲端裝置、遠端桌面等等的興起，螢幕內容視頻也漸漸普及，我們根據內容的特性將一個編碼單元分為自然內容或是螢幕內容，決定是否跳過螢幕內容編碼模式的決策，我們同樣會找尋幾個特徵，並利用SVM來做判斷，最後再結合快速深度及模式決策演算法，進一步節省計算複雜度。

High efficiency video coding (HEVC) is the latest video coding standard. The coding unit(CU) of HEVC uses a quadtree-based coding structure to increase coding performance. To improve predict more accurately, using 35 prediction modes in intra prediction. This process which is meant to improve the efficiency in HEVC intra prediction however leads to a significantly higher computational complexity. Hence, in this paper, we proposed an SVM based fast intra CU depth decision algorithm to reduce the computational complexity. We apply SVM with
features, including Variance, low-frequency AC value, and neighboring CU depth to our fast CU depth decision algorithm. In the procedure of Rate Distortion Optimization (RDO) of intra prediction, we will compare the SATD costs of all candidate modes with the smallest one. If the ratio is higher than the threshold, then we delete the modes to reduce the number of candidates for time saving.
Then we would introduce screen content coding, to diminish time consumption, the CUs can be classified into two groups, NCCU(natural content CU) and SCCU(screen content CU),according to the statistical characteristics, then we could skip screen content modes in NCCU, finally, we combine fast CU decision and fast mode decision to our screen content coding algorithm to reduce much more computational complexity.

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