視訊壓縮編碼、網路以及儲存能力的發展，使得多媒體系統的應用越來越普及與廣泛，但在頻寬的限制下讓使用者得到最好的影像品質仍一直是影像編碼的重要課題。通常，我們會使用降低畫面率或提升量化參數的方法來降低位元率。傳統的影像編碼方法通常使用非主觀品質量測如PSNR來進行評估，但在畫面率變動的狀況下，非主觀視覺品質量測無法表現出人眼所感受的影像品質。因此，使用一合適的主觀品質量測對於找出影像編碼時的最佳參數設定是必須的
在本論文中，我們的目的是找出在不同位元率下，影像的畫面率該如何設定才能產生出最佳的主觀品質量測。我們首先定義數個能反映影像本身於時間、空間上特性的參數，然後找出影像的主觀視覺品質量測與特性參數的關係式。最後，我們將提出一在影像編碼中運用此關係式以達到畫面率最佳化的演算法。
實驗結果顯示，在頻寬不足的狀況下，降低畫面率有時的確可得到比只提升量化參數還優秀的視覺品質。而演算法預測的最佳畫面率也與實際的最佳畫面率相當接近。

With the improvements of video coding technology, network infra-structures, storage capacity, and CPU computing capability, the applications of multimedia systems become wider and more popular. Nowadays, how to provide the best video quality to users under the rate constraints is always an important issue in video coding. In general, we can either increase the quantization step size or reduce the frame rate to meet the bitrate constraint. Objective quality metrics such as PSNR has long been used as the quality assessment in video coding. However, in the condition of video frame rate switching, this objective quality metric is not able to reveal the perception of human eyes. Instead, a good subjective video quality metric is necessary in helping us find the best encoding configurations.
In this work we focus on how to find the optimum frame rates in the sense of maximizing a subjective video quality metric under different rate constraints. We first characterize video sequences by parameters in temporal and spatial aspects such as edge strength, average motion vector, and motion compensation difference. Then the subjective video quality metric of a video sequence is modeled by these characteristic parameters. Finally, with this model a frame rate optimization algorithm in video encoding is proposed.
Simulation results show that reducing frame rate may be more effective than increasing quantization step size when the given bitrate is not sufficiently high. It also reveals that the frame rate provided by the proposed algorithm is very close to the ideal case.

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