Mode Decision-Based Algorithm for Complexity Control in H.264/AVC

Abstract

This paper proposes a novel complexity control method that relies on a hypothesis testing that can handle time-variant content and target complexities. Specifically, it is based on a binary hypothesis testing that decides, on a macroblock basis, whether to use a low-or a high-complexity coding model. Gaussian statistics are assumed so that the probability density functions involved in the hypothesis testing can be easily adapted. The decision threshold is also adapted according to the deviation between the actual and the target complexities.The proposed method is implemented on the H.264/AVC reference software JM10.2 and compared with a state-of-theart method. Our experimental results prove that the proposed method achieves a better trade-off between complexity control and coding efficiency. Furthermore, it leads to a lower deviation from the target complexity.

Adaptive Video Transmission Control System Based on Reinforcement Learning Approach Over Heterogeneous Networks

“…Another research area of high interest is the problem of controlling the coding rate, that is, how to reach the best video coding quality under the limits of the output coding rates. Wang et al [12], Chen et al [13], and Jimenez-Moreno et al [14] have discussed coding rate controlling methods based on the rate-distortion optimization (RDO). Harsini and Zorsi [15] studied an adaptive coding rate control algorithm based on frame complexity.…”