%0 Journal Article
%T Simulated Annealing for Land Cover Classification in PolSAR Images
%A Georgia Koukiou
%J Advances in Remote Sensing
%P 49-61
%@ 2169-2688
%D 2022
%I Scientific Research Publishing
%R 10.4236/ars.2022.112004
%X Simulated Annealing (SA) is
used in this work as a global optimization technique applied in discrete search
spaces in order to change the characterization of pixels in a Polarimetric
Synthetic Aperture Radar (PolSAR) image which ha</span><span style=\"font-family:Verdana;\">ve</span><span style=\"font-family:&quot;\"><span style=\"font-family:Verdana;\"> been classified with different label than the
surrounding land cover type. </span><a name=\"_Hlk99515879\"></a><span style=\"font-family:Verdana;\">Accordingly, Land Cover
type classification is achieved with high reliability. For this purpose, an
energy function is employed which is minimized by means of SA when the false
classified pixels are correctly labeled. All PolSAR pixels are initially
classified using 9 specifically selected types of land cover by means of Google
Earth maps. Each Land Cover Type is represented by a histogram of the 8
Cameron¡¯s elemental scatterers by means of coherent target decomposition (CTD).
Each PolSAR pixel is categorized according to the local histogram of the
elemental scatterers. SA is applied in the discreet space of nine land cover
types. Classification results prove that the Simulated Annealing approach used
is very successful for correctly separating regions with different Land Cover
Types.
%K Land Cover Classification
%K Simulated Annealing
%K Fully Polarimetric SAR
%K Co-herent Decomposition
%K Elemental Scatterers
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=117774