| dc.description.abstract | H.264/AVC has become the most frequently used video codec nowadays. A lot of efforts have been made to pursue highly efficient video coding and to maintain good rate-distortion performances of video compression. In this dissertation, several content-adaptive models are developed to increase the speed of video encoding and to achieve better rate/quality control in H.264/AVC. The dissertation consists of three major parts. First, an efficient intra-prediction mode decision mechanism is presented. A projection-based approach, which utilizes the reconstructed surrounding pixels and block content to compute the predicted block residuals (PBR), can effectively eliminate the less probable modes from the computation of Rate Distortion Optimization. According to the PBR and coding information acquired during the encoding process, some prediction modes and macroblock types can be further skipped to accelerate the intra coding. Then, after considering the efficiency of intra coding, we research the issue of Rate-Quantization (R-Q) in the intra coding of H.264/AVC. Assigning an appropriate Quantization Parameter (QP) to the intra-coded frames is very important to the video coding. A content-adaptive R-Q model is thus presented to predict the bit usage of intra-coded frames. The relationship between the QP of a macroblock and the block complexity is derived so that a suitable QP can be determined under a target bit-rate. Since the proposed model is built on macroblocks, Region of Interest (ROI) coding can also be achieved. By adjusting the QP value at the macroblock level, more bits can be assigned to the ROI to better preserve its perceptual quality. Finally, we tackle the problem of rate/quality control for regular video encoding by estimating the resultant quality or distortion associated with QP. A Distortion-Quantization (D-Q) model is proposed to predict the distortion level, which is defined as the difference between the original video frame and the decoded one in the sum of squared errors. As in the R-Q model, the proposed D-Q model also has only one adjustable parameter related to the macroblock content and provides a mapping between QP and the corresponding distortion before the exact encoding process. Given a targeted frame quality measured in peak signal to noise ratio (PSNR), this model helps to assign a suitable QP value to each frame. Two applications are then considered, i.e., the single-pass constant frame PSNR coding and the two-pass coding with the additional bitrate or storage constraint, both of which can facilitate such applications of video archiving and editing. | en_US |