In lossy image/video encoding, there is a compromise between the number of bits and the extent of distortion. Optimizing the allocation of bits to different sources, such as frames or blocks, can improve the encoding performance. In intra-frame encoding, due to the dependency among macro blocks (MBs) introduced by intra prediction, the optimization of bit allocation to the MBs usually has high complexity. So far, no practical optimal bit allocation methods for intra-frame encoding exist, and the commonly used method for intra-frame encoding is the fixed-QP method. We suggest that the QP selection inside an image/a frame can be optimized by aiming at the constant perceptual quality (CPQ). We proposed an iteration-based bit allocation scheme for H.264/AVC intra-frame encoding, in which all the local areas (which is defined by a group of MBs (GOMBs) in this paper) in the frame are encoded to have approximately the same perceptual quality. The SSIM index is used to measure the perceptual quality of the GOMBs. The experimental results show that the encoding performance on intra-frames can be improved greatly by the proposed method compared with the fixed-QP method. Furthermore, we show that the optimization on the intra-frame can bring benefits to the whole sequence encoding, since a better reference frame can improve the encoding of the subsequent frames. The proposed method has acceptable encoding complexity for offline applications.

Modern video compression usually consists of ME/MC (Motion Estimation/Motion Compensation), transform, and quantization of the transform coefficients. Efficient bit allocation technique to distribute available bits to motion parameters and quantized coefficients is an important part of the whole system. A method that is very complex and/or needs buffering of many future frames is not suitable for real time application. We develop an efficient bit allocation technique that utilizes the estimated effect of allocated bits to motion parameter and quantization on the overall quality. We also propose an hierarchical block based ME/MC technique that requires less computations than classical BMA (Block Matching Algorithm) while offering better motion estimation.