Underwater Image Enhancement Using Gaussian Smoothing and Edge Detection

Underwater acoustic communication is used for oceanographic data collection, environmental monitoring, disaster alarm systems, and navy applications. Underwater has its peculiarities such strong signal attenuation and limited bandwidths, multipath nature of signals, and ambient noises. All these characteristics bring a great deal of interference probably in transmission with certainty and effectiveness. This work propounded an optimized hybrid model that works concurrently with advanced signal processing and noise-reducing techniques for communication enhancement. The purpose of the proposed model is to develop high signal-to-noise ratio (SNR) received signals with lesser transmission error using time-frequency domain analysis and filtering techniques, which are specifically designed for underwater applications. Thus, the main aim of this work, in fact, is towards the development of a robust underwater communication platform, which ensures a very reliable transfer of data under conditions of excessive noise even in the rapidly changing aquatic environments. Comparison of the proposed model with traditional techniques shows that this model stands much higher than the earlier techniques regarding transmission accuracy, noise resilience, and overall efficiency, thus extending the development of more reliable underwater communication systems toward future marine and defense applications.