Hyperspectral imaging is widely used in various fields. This thesis refers to a specific remote sensing application. It aims to find and implement an algorithm able to compress hyperspectral images which are used to detect the presence of ice on metallic surfaces. The basic concept is that different materials bring to different spectral signatures, which allows us to recognize them through specific software. A hyperspectral image is obtained with a special camera which collects information of the same spatial scene at different spectral bands, i.e. narrow portions of the electromagnetic spectrum. As a consequence, the amount of data to be processed is huge, and has to be reduced without losing essential information for spectral recognition.