Contact
sivert.bakken@ntnu.no

At the NTNU SmallSat Lab We have developed HYPSO-1 a CubeSat equipped with a powerful
hyperspectral camera. Hyperspectral imaging is a powerful tool for remote sensing and imaging applications, which collects large amounts of data at various wavelengths. The data collected by hyperspectral imaging sensors are usually in high-dimensional spectral data cubes, which require significant storage space and computational resources for processing and analysis. Miniaturized hyperspectral imaging sensors have gained significant attention recently due to their reduced size, weight, and power consumption. This project aims to develop an optimal data reduction method for a miniaturized hyperspectral imaging sensor. The proposed method will reduce the amount of data the sensor collects while retaining the essential information required for further analysis. The data reduction method could employ advanced signal processing and machine learning techniques to compress the hyperspectral data cubes into a compact and informative representation.