本論文提出一個結合內容相關位元率量化模型與興趣區域之H.264/AVC畫面內預測編碼。在視訊編碼的位元率控制中，畫面內預測編碼佔了很重要的地位，其過高或過低的位元率將影響整體的編碼效率。在本篇論文中，我們提出了一個較準確的畫面內預測位元率量化模型(Rate-Quantization model, R-Q model)。我們根據區塊內容的複雜度與目標之位元率，求得此區塊之編碼率與量化參數(Quantization Parameter, QP)值的相對應關係。此外，在有了此內容相關位元率量化模型後，我們可結合興趣區域編碼，使得本機制在有限的位元率下，於興趣區域給予較多位元數，也就是較低之QP值，而使其具有較佳的畫質，而在視覺較不注意之區域給予較少位元數，藉由內容相關位元率量化模組與興趣區域的結合能在有限之位元數下達到較佳的人眼視覺效果。我們將畫面分成三個區域以各自給予適當的QP值。我們的實驗顯示，整體畫面平均之峰值訊號雜訊比 (Peak Signal to Noise Ratio, PSNR) 雖下降0.27 dB，但人眼視覺最關注區域之PSNR值增加了1.2 dB，而人眼最關注的前兩個區域則增加了0.51 dB。與傳統畫面階層之R-Q model相較，此區塊階層之R-Q model更具彈性，更容易達到目標位元率。 This thesis presents a joint content adaptive rate-quantization model and region of interest intra coding of H.264/AVC. The rate control of video coding is an important issue and the intra coding plays a very crucial role. Inappropriate assignment of bitrates in intra coding will deteriorate the overall coding performance. We will first present a more accurate content adaptive Rate-Quantization (R-Q) model, by which we can obtain the relationship between the Quantization Parameter (QP) of a macroblock and the block complexity. Given a target bit-rate, we can thus assign a more suitable QP for a frame. In addition, since our model is built on blocks, or more specifically macroblocks, Region of Interest (ROI) coding can also be achieved. More bits can be assigned to the ROI by using a lower quantization parameter (QP) so that the perceptual quality can be maintained within the limited bit-rate. Our macorblock-level R-Q model, compared with the traditional frame-level RQ model, is more flexible and can achieve the target bit rate more accurately.
