Spectral Imaging

Spectral imaging captures information across multiple wavelengths, enabling material identification and analysis beyond the capabilities of standard cameras. Current research focuses on improving the efficiency and accuracy of spectral image acquisition and reconstruction, employing techniques like compressive sensing, deep learning models (including convolutional neural networks and transformers), and novel camera designs to reduce data size and computational burden. These advancements are driving progress in diverse fields, including medical imaging, remote sensing, and industrial inspection, by providing richer, more informative data for analysis and improved diagnostic capabilities.