This work presents a new methodology for the automated inspection of nuclear fuel pellets based on Single Image Super Resolution (SISR) and Hyperspectral Imaging (HSI). HSI technology provides optical images in which the pixels contain comprehensive spectral information, normally hundreds of channels (wavelengths) covering the Visible Near InfraRed (VNIR) region in the electromagnetic spectrum. Therefore, the spectral information provided by HSI can be used for inspecting images of pellets pixel-wise. However, the spatial resolution in HSI is lower in comparison to conventional imaging, and SISR is proposed for enhancing the HSI images. Results showed how techniques such as Principal Component Analysis (PCA) can be applied to SR-HSI images to effectively exploit the HSI spatialspectral content and generate maps for the automated detection of potential abnormalities on the surface of nuclear fuel pellets. While experiments used color chalk as analogues of PWR pellets, results with sintered UO2 will be presented at the conference.