Sonar Image

Sonar image analysis focuses on extracting meaningful information from acoustic images of underwater environments, primarily for autonomous navigation, object recognition, and mapping. Current research emphasizes developing robust feature detection and matching algorithms, often employing convolutional neural networks (CNNs), graph attention networks (GATs), and transformers, to overcome challenges like noise, multipath interference, and limited texture. These advancements are crucial for improving the capabilities of autonomous underwater vehicles (AUVs) in various applications, including underwater exploration, inspection, and environmental monitoring.