Ant weight-lifting algorithm for motion estimation - Acharjee, Suvojit; Chaudhuri, Sheli Sinha (Iran Journal of Computer Science (Online), 2023)
Every video coding standard includes and requires motion estimation and compensation. The full search algorithm, which provides the best motion estimation, has a very high computation cost. Researchers have developed several algorithms to reduce the cost of computation. However, most of these algorithms become trapped in local minima during the search. Population-based evolutionary algorithms are widely used to develop a computationally efficient and cost-effective motion estimation strategy. The most recent effort used the Jaya algorithm to develop a motion estimation process that outperformed the state-of-the-art test zone search algorithm. In this study, a motion estimation algorithm based on the ant weight-lifting approach is proposed. Previously, the ant weight-lifting algorithm was used to solve a variety of problems, such as image segmentation, signal compression, and so on. The ant weight-lifting algorithm's computation cost was reduced by adopting a fitness estimation method that uses nearest-neighbor interpolation and an early termination strategy. Compared to Jaya algorithm-based motion estimation, the proposed algorithm executes up to 3% more quickly and exhibits up to 1.2 dB less distortion.