Multispectral Camera

Multispectral cameras capture images across multiple wavelengths of the electromagnetic spectrum, providing richer information than conventional cameras. Current research focuses on improving data processing techniques, including advanced algorithms like deep learning (e.g., UNets, Transformers) and classical methods (e.g., SVM, K-means++) for tasks such as noise reduction, image segmentation, and object detection in diverse applications. These advancements are driving improvements in fields like agriculture (crop monitoring, precision farming), remote sensing (water quality monitoring, forest health assessment), and planetary science (mineral mapping, lander site selection), enabling more accurate and efficient data analysis. The development of compact, cost-effective multispectral cameras, particularly in the longwave infrared, is also an active area of innovation.