Buffer control in H.264/AVC applications by implementing dynamic complexity-rate-distortion analysis

In this work we present a novel optimal buffer control approach for H.264/AVC low-delay applications by dynamically allocating computational complexity (such as a number of CPU clocks) and bits for encoding each coding element (basic unit) within a video sequence, according to its predicted MAD (Mean Absolute Difference), while considering buffer size limitations (preventing underflow/overflow of the buffer) and buffer delay. Our buffer control approach is based on a computational complexity-rate-distortion (C-R-D) analysis, which adds a complexity dimension to the conventional rate-distortion (R-D) analysis. Both theoretically and experimentally, we prove that by implementing the proposed buffer control approach better results are achieved. In addition, we present an optimal buffer control method and system for implementing the proposed approach, and for controlling computational complexity and bit allocation in real-time and off-line video coding. We divide each frame into one or more basic units, wherein each basic unit consists of at least one macroblock (MB), whose contents are related to a number of coding modes. We determine how much computational complexity and bits should be allocated for encoding each basic unit, while considering buffer size limitations and buffer delay, and then we allocate a corresponding group of coding modes and a quantization step-size, according to the estimated distortion (calculated by a linear regression model) of each basic unit and according to the remaining computational complexity and bits for encoding remaining basic units. For allocating a corresponding group of coding modes and the quantization step-size, we develop computational complexity - complexity step - rate (C-I-R) and rate - quantization step-size - computational complexity (R-Q-C) models.