在高動態或是變換場景的影片中，由於傳統的編碼架構無法將各張影像維持在相近的品質之下，大幅降低了影片的觀看品質。最近，植基於H.264視訊壓縮標準，Huang與Hang提出網格式一致性品質控制演算法來提高視訊影片的觀看品質。其方法將穩定影像品質的問題轉化為網格式的樹狀架構，從樹中尋找相同影像品質的最佳路徑，完善控制每一張影像的品質，然而其方法的計算複雜度相當高。本篇論文提出了一個改良式失真模型來大幅降低品質控制演算法所需的要的運算量。我們利用失真模型來預估不同量化參數可能產生的失真值，剃除失真值不滿足條件的分支，減少多餘的編碼程序。實驗結果顯示，與Huang和Hang提出的演算法相較之下，我們提出的一致性影像品質控制演算法，平均可節省47%的編碼時間。同時，在影像品質方面，新的演算法平均僅有0.1dB左右的PSNR損失，可達到與原方法相同的視覺品質。

The traditional video coding techniques are difficult to achieve the consistent quality for video with high motion or frequent scene changes. Thus, that significantly reduces the viewing quality. Recently, Huang and Hang proposed a trellis-based algorithm for consistent quality control in H.264/AVC and it can improve the visual quality of the encoded video sequences significantly. Converting the quality consistency problem to that of finding an optimal path in a tree, the trellis-based algorithm encodes each encode in a consistent quality. However, the trellis-based algorithm suffers from time-consuming problem since it spends a lot of computation time in the tree construction process. In this paper, we develop an improved distortion model to reduce the computational complexity of trellis-based consistent quality control algorithm. Based on the proposed distortion model, we can predict the distortion of current frame caused by a specific quantization parameter. The predicted distortions of different quantization parameters can be used to remove unnecessary encoding procedures and it leads to a significant computation saving-effect. Experimental results demonstrate that the proposed fast consistent quality control algorithm has 47% execution-time improvement ratio and results in less than 0.1 dBs PSNR degradation when compared to Huang and Hang’s algorithm. As for the visual quality comparison, our proposed fast algorithm has the same quality as Huang and Hang’s algorithm.

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