In this paper, we propose power efficient motion estimation (ME) using multiple imprecise sum absolute difference (SAD) metric computations. We extend recent work in [18] by providing analytical solutions based on modelling of computation errors due to voltage over scaling (VOS) and sub-sampling (SS). Results show that our solutions provide significantly better performance in the sense of rate increase for fixed QP, e.g., less than 5% increase, while in [18] the rate increase could be as high as 20%. Our analysis also allows us to compare different ME algorithms (e.g., full search vs. a fast algorithm) and SAD computation architectures (parallel vs. serial) in terms of their robustness to imprecise metric computations and their power efficiency. Finally, we demonstrate that additional power savings can be achieved by removing redundancy between the various computations.