Enhanced dynamic pattern search algorithm with weighted search points for fast motion estimation

Abstract

For video encoding, a number of block-based motion estimation techniques have been proposed in the literature. Some of them are based on fixed search patterns, whereas others are utilizing spatial and temporal correlations of blocks within video frames. It has been found that the block correlations give an initial lead in identification of motion vector of the candidate block and the possibility of oversearch or undersearch is minimized. In this paper, the dynamic pattern search (DPS) algorithm for block-based motion estimation has been enhanced which reduces the search point computation by first identifying the stationary blocks. Further, in the proposed algorithm, search points within the search area are evaluated for minimum distortion point in prioritized fashion to reduce the possibility of being trapped in local minima. The proposed work has been compared experimentally with fixed search pattern techniques like full search, diamond search (DS) and hexagon search and adaptive search pattern techniques like adaptive rood pattern search and DPS in terms of various performance parameters. It has been found that the proposed technique is faster by 6.32 and 3.30 times than DS and DPS techniques in terms of avg. search point computation per block and produces better peak signal to noise ratio than DS and DPS by the value of 1.03 and 0.63 dB, respectively. In terms of structural similarity measurement index value, enhanced DPS gives 8% better results than DPS and performs better compression than any other technique except FS.