An Improved Block-Matching Algorithm Based on Chaotic Sine-Cosine Algorithm for Motion Estimation

Motion estimation (ME) plays an important role in a video coding solution to achieve a low bit rate. The selection of the optimal motion vector (MV) has a significant impact on the quality of the compressed video. Block-matching (BM) algorithm is one of the widely accepted ME techniques to estimate the motion between the successive frames. In any BM technique, the motion vectors (MVs) are obtained for the current frame over a pre-defined search region in the previous frame by minimizing certain matching criterion. However, the computation of these matching criteria is highly expensive (in terms of the computational time). Hence, the block-based ME (BME) can be realized as an optimization problem which aims at finding the best-matched block within a specified search region. In this context, an improved block-matching technique is proposed that incorporates a chaotic-based sine-cosine optimization algorithm along with a fitness approximation (FA) strategy. The proposed approach has been compared with several other BM techniques in terms of different parameters, namely, the peak-signal-to-noise-ratio (PSNR), PSNR degradation ratio (\(D_{PSNR}\)), and the number of search points. The analysis of the results obtained demonstrates that the proposed method yields potential improvements over other competent schemes.