Spectral Correlation

Spectral correlation analysis in hyperspectral imaging (HSI) focuses on exploiting the inherent relationships between spectral bands and spatial locations within HSI data to improve various image processing tasks. Current research heavily emphasizes the development of advanced deep learning models, including transformers and state-space models like Mamba, to efficiently capture these complex correlations for applications such as denoising, reconstruction, and classification. These advancements lead to improved accuracy and computational efficiency compared to traditional methods, impacting fields like remote sensing, medical imaging, and computational photography by enabling higher-quality image analysis and more robust algorithms.