Mathematical Modelling of Nonlinear Approach in Video Compression for Telecommunication

Abstract

The rapid evolution of telecommunication systems necessitates efficient video compression techniques to optimize bandwidth utilization and enhance multimedia experiences. This paper introduces a hybrid nonlinear analytical approach to video compression tailored for real-time telecommunication applications. The approach integrates Block Matching Motion Estimation (BMME) techniques using a fusion of Efficient Three-Step Search (ETSS) and Hexagonal Search (HS) algorithms. This combination significantly reduces data redundancy, minimizes the number of search points, and improves video quality with lower computational overhead. The proposed model is grounded in mathematical principles of motion estimation, compensation, and prediction, supported by statistical metrics including SAD, MAD, MSE, PSNR, and Compression Ratio. Through experimentation on diverse standard video datasets, the hybrid method consistently outperformed traditional techniques in terms of accuracy and efficiency. Literature reviews confirm the growing relevance of hybrid and adaptive video compression frameworks in dynamic network environments. This research contributes a robust, scalable solution that meets the demands of modern telecommunication networks, paving the way for future innovations in real-time, high-quality video transmission.