Parallel video coding has recently received considerable attention since there is a strong need for real time applications. To resolve the extremely high computational complexity of Motion Estimation as a most time consuming part of the video coding, suitable parallel algorithms need to be developed. Recently, the use of Graphics Processing Units (GPUs) for parallel tasks has become popular. Motion estimation as a most important part of the video coding standard is readily parallelized. Thus, this task is well-suited for GPU based parallel implementation. In this paper, three GPU based parallel approaches of motion estimation are introduced. In all of these algorithms, the motion information is analyzed and dynamic search areas are employed. In another approach, we make use of the combined CPUs and GPU system in order to reach more effective results especially in the case of real time applications for devices with limited computational resources. The results of the combined method are superior especially for medium amount of motion. The experimental results show appropriate performance of the presented approaches in both PSNR values and speedup.
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