Abstract / truncated to 115 words (read the full abstract)

THIS doctoral thesis attemps to propose a novel signal processing chain, aimed to exploit data acquired by long wave infrared (LWIR) hyperspectral sensors. In the LWIR, infrared radiation from an object is directly related to its temperature, i.e. hotter the surface, higher the emitted thermal energy. Hyperspectral sensors capture the radiated energy from the objects (target) in a large number of consecutive spectral bands within the LWIR, e.g. with the aid of a prism, in order to estimate the spectrum(spectral emissivity) and the temperature of the surface material. In this framework, two main challenging tasks affect the development and the deployment of thermal hyperspectral sensors: - atmospheric correction: the process of estimate and compensate the ... toggle 6 keywords

hyperspectral remote sensing LWIR thermal infrared target detection temperature and emissivity separation alpha residuals


Moscadelli, Matteo
University of Pisa
Publication Year
Upload Date
May 22, 2020

First few pages / click to enlarge

The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.

The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.