A novel search method based on artificial bee colony algorithm for block motion estimation - Weiyu Yu; Dan Hu; Na Tian; Zhili Zhou (EURASIP Journal on Image and Video Processing, 2017)
Abstract The large amount of bandwidth that is required for the transmission or storage of digital videos is the main incentive for researchers to develop algorithms that aim at compressing video data while keeping their quality as high as possible. Block matching has been extensively utilized in compression algorithms for motion estimation as they reduce the memory requirements of any video file. A novel method by using modified artificial bee colony algorithm (MABCA) is proposed, which is the combination of basic ABCA and several techniques—initialization based on temporal-spatial correlation, duplicate searching avoidance technique, adaptive search criteria for iteration, and early termination of block matching. Experimental results show that the proposed method has achieved significant improvement over the existing popular block-matching methods in terms of estimation accuracy and computational complexity, especially when dealing with sequences with violent motion. This method can also adaptively adjust the average search point number according to the motion intensity of the different sequences in order to get the best search result at the lowest possible cost.