高效率視訊編碼標準，又稱為HEVC，是目前最新的編碼技術標準，由ITU-T與MPEG兩個組織在2013年的4月共同制定完成。當HEVC出現後，為了開發不同的應用，許多流量控制的演算法也被研發出來。在HEVC這個標準出現之前，已經有許多知名的流量控制演算法，如某些演算法建構在R-Q原型上，這些方法認為流量R與量化系數Q有很大的關係。而在近期，另一個建構在R-λ原型上的演算法被提出，這個方法認為流量R與Langrance系數λ有更明確的一個縣性關係。這個演算法目前也被HEVC的最新版官方軟體HM10.0所採用。但這一個演算法在針對低流量編碼時會有流量控制失敗與不穩的問題。這個問題主要是因為這一個演算法並沒有將視訊內容加入公式考量。
在這一篇論文中，我們提出了另一個建構在R-λ原型上的演算法，這個演算法成功的消除了在低流量編碼時會出現的問題。透過觀察影像當中的合併資訊，我們發現這些資訊與壓縮時的流量有很大的關係。另外也有一些其他的方法如ROI配合特徵圖的方法也可以找出影像當中的資訊。但根據我們的實驗，我們將非合併資訊畫出的圖與真正的特徵圖做比較，兩張圖是非常的類似且重疊。因此在這一篇論文中我們提出的方法是以非合併模式資訊為基礎之高效率視訊編碼的R-λ流量控制演算法。除此之外，我們也針對不同的編碼層提出了新的流量分配的方法，這個方法將能夠使得影像的品質提高。在實驗結果當中我們將能夠看到我們的方法成功的降低了流量控制的錯誤率，以及在同樣的流量底下拉高了影像品質。

The H.265 (high efficiency video coding, HEVC) standard was finalized in April 2013, currently being as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Expert Group. When HEVC has been emerged, several rate control algorithms are being developed for practical applications, especially in real-time streaming services. There are some of the existing rate control algorithms based on the R-Q model, which is considered having a solid relationship between streaming bitrate R and playback quality Q. Recently, a promising R-λ model, which having a more robust correspondence between R and Langrance multiplier λ, was proposed and adopted by HEVC reference software HM10.0. However, this general R-λ model does not perform well in the sense of frame rate prediction especially for low bitrate sequences. That is because the content (image frame) variation does not being included in the model function. In this study, an enhanced formula is proposed to remedy those ill-conditioned situations. By observation of the number of non-merge PU in all of coded frames, there has a great connection on the real bitrate cost noticeably. Another way of exploring the content variation is to uncover the ROIs (typically, people or faces) with saliency map. In our experience, the plot of non-merged PUs is quite similar to that of ROIs. In this thesis, an enhanced R-λ rate control modelling using non-merge information is proposed. Also, an alternative bit allocation coding tree unit (CTU) level is developed for enhancing the quality of ROIs. The experimental results show that the proposed method can reduce the bit-rate estimation error and improve the video quality in video conference test cases.
Index Terms－HEVC, R-λ model, rate control, ROI, saliency map, merge mode

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