Most existing hyperspectral anomaly detection methods are developed and validated on numerical datasets, focusing on simulations rather than practical applications. To bridge this gap, we introduce an ...

Existing deep learning-based hyperspectral anomaly detection methods often overlook frequency domain features, hindering the ability to effectively distinguish between background and anomalies.