The proposed algorithm is an early termination scheme based on threshold values obtained through fuzzy inference. Using the search patterns of the MDGDS algorithm, we employed the scale factors of fuzzy inference on the three round alternative search pattern on MDGDS. Whether the search is to be terminated early is determined prior to each round of the search process to prevent unnecessary computation. Actual test results indicate that the proposed algorithm can reduce the significant number of search points in average, compared to MDGDS. The proposed algorithm makes significant improvements in motion estimation.
To enhance the DGDS algorithm, this paper presents an efficient algorithm named modified directional gradient descent searches (MDGDS). By analyzing the statistical best MV distribution on some well-known test video sequences, a new search pattern is derived with three search rounds including the window center area, cross area and diagonal area based on stationery and quasi-stationery characteristics. Early search termination operations are then applied to the new search pattern before performing DGDS to eliminate unnecessary computations. The enhanced MDGDS algorithm develops a content adaptive technique based on the previously coded frame for early termination thresholds selection to avoid being trapping in local minima. The simulation results show the proposed algorithm provides significant improvement in reducing the motion estimation by about 19% of the average search points saving compared to the fast DGDS algorithm according to different types of sequences, while maintaining a similar bit-rate without losing picture quality.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.