數位視訊需經有效的資料壓縮程序以利其傳輸與儲存。然而，壓縮後的視訊畫質並不易受到控制，連續畫面品質的劇烈變動，可能造成若干視覺上的失真。若相關應用需要將每張畫面內容適當地保存，只考慮位元率控制的編碼機制也許並不是非常適合。本研究提出視訊畫質恆定控制技術，減少視訊畫面間的品質差異，提升視訊觀賞的流暢度與舒適感，有利於重要資料的保存。此外，如果我們能夠在編碼前即合理預測視訊畫質與編碼參數間的關係，對於位元率控制編碼也將有所助益。 以往的視訊畫質估測經常採用均方誤差的方式，但均方誤差與人眼視覺之間缺乏良好的相關性。因此研究人員提出了各種畫質估測方式，而結構相似性指標(SSIM)是其中之一。由於結構相似性指標有效地模擬人眼視覺系統中擷取影像結構訊息的功能，所以我們採用結構相似性指標做為畫質量測依據，並藉此提出失真-量化參數預測模型、模型參數的預測方法以及實際編碼中的動態處理程序等，以達成畫面品質恆定控制之目的。與H.264/AVC參考軟體JM相較，我們所提出的方法不僅大幅降低了畫面品質的變化，在同樣的整體視訊品質下，也擁有較低的位元率。 The digital videos require effective compression to facilitate their transmission and storage. However, it is not easy to control the quality of compressed videos. If the related applications need to preserve the content of every frame in the video, the traditional rate control mechanism may not be suitable. In this research, we propose a constant frame quality control technique, which can reduce the quality variations between successive frames to avoid serious perceptual distortion. The proposed scheme may thus be helpful in the applications of video archiving or surveillance videos. In addition, by constructing the relationship between the quality and quantization parameter, the proposed method may also benefit the traditional rate control coding. Objective distortion metrics such as mean squared error or peak signal to noise ratio are poorly correlated with the human perceptual quality. Recently, various image/video quality metrics based on the HVS have been proposed and the structural similarity (SSIM) index has been shown to be effective. Therefore, we adopt SSIM as the quality metric for our constant frame quality control. Compared with the reference software of H.264/AVC, JM, our approach can reduce SSIM variation significantly. Furthermore, at the same SSIM index, the proposed scheme achieves lower overall bit-rate.
