A new one-pass Complexity-Scalable computation-control method for video coding
In this paper, a new Complexity-Scalable computation control method is proposed which can perform Motion Estimation (ME) adaptively under different computation or power budgets while keeping high coding performance. We first propose a new class-based method to measure the Macroblock (MB) importance where MBs are classified into different classes and their importance is measured by combining their class information as well as their initial matching cost information in the ME. Based on the new MB importance measure, a computation control framework is then proposed to allocate computation for ME. Experimental results demonstrate that the proposed method can allocate computation more accurately than previous methods and thus has better performance under the same computation budget.