Robust phase extraction from complex signals/fringe patterns for optical communications in 5G and beyond through continuous wavelet ridge technique

The rapid progress in high-precision optical instruments necessitates sophisticated image processing techniques for extracting vital information from generated images. Most of these instruments output images comprising RGB pixels. Deciphering these pixel values into phase information poses a significant challenge, especially in the presence of background noise. This study focuses on utilizing Two-Dimensional Continuous Wavelet Transforms (2-D CWT) for analyzing fringe patterns with varying noise levels and fringe alignments, crucial for high-precision optical systems pivotal in enhancing the performance and reliability of optical communication systems in advanced 5G networks. The simulation results demonstrate that 2-D CWT efficiently extracts phase information from complex and highly noisy fringes while requiring less computational time. Furthermore, the algorithm effectively handles noise disturbances with a commendable degree of accuracy, ensuring robust performance in 5G-enabled optical systems critical for supporting ultra-high-speed data transmission and low-latency communication requirements. This research contributes to optimizing image analysis techniques for 5G optical systems, facilitating their integration into next-generation communication networks.