A High Quality/Low Computational Cost Technique for Block Matching Motion Estimation
Proceedings of the conference on Design, Automation and Test in Europe - Volume 3
Efficient motion estimation algorithm using run-time and distortion optimization approach
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Multi step motion estimation algorithm
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Configurable complexity-bounded motion estimation for real-time video encoding
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Low level analysis of video using spatiotemporal pixel blocks
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
A multi-processor NoC-based architecture for real-time image/video enhancement
Journal of Real-Time Image Processing
Hi-index | 0.01 |
The full search motion estimation algorithm for video coding is a procedure of high computational cost. For this reason, in real-time low-power applications, low-cost motion estimation algorithms are viable solutions. A novel reduced complexity motion estimation algorithm is presented. It conjugates the reduction of computational load with good encoding efficiency. It exploits the past history of the motion field to predict the current motion field. A successive refinement phase gives the final motion field. This approach leads to a sensible reduction in the number of motion vector that have to be tested. The complexity is lower than any other algorithm algorithms known to the authors, in the literature, it is constant as there is no recursivity in the algorithm and independent of any search window area size. Experimental evaluations have shown the robustness of the algorithm when applied on a wide set of video sequences-a good performance compared to other reduced complexity algorithms and negligible loss of efficiency versus the full search algorithm