本論文中，提出一套改進後的位元率控制演算法流程，利用stochastic subgradient method動態地調整拉哥朗日乘數λ。以合適的λ值在位元失真最佳化過程才能選擇到最佳的編碼方式。利用修正後的λ值決定每一個編碼區塊的最佳量化參數，我們提出一個對數型態的QP-λ線性模型，根據λ預測編碼區塊的量化參數，並以較小的搜尋範圍找出最佳量化參數，取代搜尋所有量化參數造成的龐大計算負擔。基於上述兩種方法我們提出一套區塊層級的位元率控制流程，在每次編碼完成後，使用實際產生的位元量來更新下一塊編碼區塊的λ值。我們所提出的演算法修改在H.264/AVC的參考軟體並與之比較，實驗結果證明不論在CIF和HD1080p格式的測試影像，提出的演算法皆能提升編碼器的R-D performance，並且降低輸出位元率與目標位元率之間的誤差，準確地控制編碼後產生的位元率。此外，我們提出的方法能以較簡單的模型和計算來決定量化參數和拉哥朗日乘數，不僅提升編碼表現，更降低整體編碼時間。

In this paper we propose to improve the performance of the rate control mechanism in video encoders by adaptively adjusting the Lagrange multiplier λ based on the stochastic subgradient method. Using this λ value for each coding unit, the quantization parameter is sought in the process of rate-distortion optimization. A log-linear model can be utilized to predict the most probable quantization parameter and accordingly narrow the search range. The generated bit number is used to update the λ-value for the next coding unit. Extensive experimental results show that the proposed rate control mechanism significantly enhances the rate-distortion performance compared to the H.264/AVC reference software in CIF and HD1080p format sequences. The error between output bit rate and target one is reduced, which proves proposed method controls the bit rate accurately. In addition, the proposed method determines the quantization parameter and Lagrange multiplier easily by a simple model and computations, which further reduces the encoding time.

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