Content Adaptive Motion Estimation for Mobile Video Encoders

Power consumption has emerged as an important constraint in the design of mobile video encoders. As motion estimation accounts for the majority of the total computations involved in video encoding, the algorithm and architecture used affect the quality and power levels of the final solution. In this paper, we present a block matching motion estimation algorithm whose computations are content complexity adaptive. The basic framework used is the multi-resolution mean pyramid technique. The algorithm is made macroblock adaptive by dynamically varying the number of candidate motion vectors passed to lower levels, depending on the frequency characteristics of the macroblock being matched and the complexity in the sequence for such characteristics. We use the concept of a deviation pyramid in order to estimate the macroblock frequency characteristics. Simulation results show that for typical videophony sequences, the algorithm reduces computational complexity by a factor ranging from 15.5 to 74.0, while maintaining PSNR values close to that obtained by using the full-search block matching algorithm. Simple operations are used in the algorithm to ensure applicability of the proposed algorithm for hardware implementation