26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Türkiye, 2 - 05 Mayıs 2018, ss.1-5, (Tam Metin Bildiri)
One of the global issues that threatens human and environmental health is the harmful substances leaking to the atmosphere as a result of industrial, agricultural and other activities. These substances intensively contain gaseous, such as; water vapor, carbon dioxide, methane, nitrogen oxide and ozone that cause greenhouse effect. Due to the high-resolution information provided in both spatial and spectral domains, hyperspectral imagers have recently been used as an alternative method for standoff detection of these substances. The methods proposed in the literature use atmospheric models or estimation methods to obtain crucial parameters that are required for modelling the measured radiance. In this study, we propose a method to detect and identify greenhouse gaseous, which are released from different sources, that does not require the such parameters for modelling the measured radiance.