Adaptive two-step edge-based partial distortion search algorithm using motion vector prediction

Motion estimation is a core process within video coding schemes, because it enables the transmission and storage of video signals, while using a lower bit rate. Various methods have been proposed for motion estimation. A full search algorithm is considered to be the optimal method, but it suffers from a high computational burden. In order to reduce the computations, this paper proposes an adaptive two-step edgebased partial distortion search algorithm. The proposed algorithm reduces computations by reducing the total search point and adjusting the search range. The proposed algorithm is 147 times faster than full search (FS), 12 times faster than normalized partial distortion search, and 1.75 times faster than a two-step edge based partial distortion search (TS-EPDS). It also shows a high video quality, in comparison with FS, in terms of PSNR. The proposed algorithm is suitable for real-time implementation of high-quality digital video applications.