As multimedia communication has become important, efficient image compression has received increasing attention. In this thesis, we propose several bit allocation schemes for image/video coding based on a rate-distortion sense.
To improve the quality of the reconstructed image for a given bit rate constraint, the bit budget must be distributed efficiently among a set of given admissible quantizers. This bit allocation scheme for source coding is based on Shannon``s rate-distortion theory, which deals with minimization of source distortion subject to a channel rate constraint. To allocate a given quota of bits to an arbitrary set of different quantizers, a dynamic programming method was suggested for rate control based on rate-distortion characteristics. Since this optimal method requires large computational complexity, however, several fast algorithms for optimal bit allocation have been proposed. But these algorithms are still not fast enough for the practical implementation in image codings. In this thesis, we propose a new fast algorithm for optimal bit allocation, which reduces the computational complexity drastically compared to conventional fast algorithms.
In real-time video coding, the proposed optimal bit allocation algorithm is still not fast enough. Therefore we suggest a suboptimal algorithm, or an efficient rate control algorithm, which can improve the performance of the MPEG-2 for a given bit rate constraint. The proposed algorithm is based on the fine adjustment of the quantization parameter of each region by examining the distortion-rate curve. It can be easily applied to existing MPEG coders by adding a reasonable size of hardware. Simulation results show that the performance of the algorithm is better than the rate control algorithm in the MPEG-2 Test Model 5.
Appropriate target-bit assignment to each picture in the group of pictures (GOP) is also an important issue for video coding efficiency. A new target-bit allocation, which is based on...