Title :
Comparative algorithms for automatic detection of oil spill in multisar of RADARSAT-1 SAR and ENVISAT data
Author :
Marghany, Maged ; Hashim, Mazlan
Author_Institution :
Inst. of Geospatial Sci. & Technol. (INSTeG), Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
This study presents a comparative algorithms for oil spill automatic detection from different RADARSAT-1 SAR different mode data and ENVISAT ASAR data. Three algorithms are involved: Entropy, Mahalanobis, and Artificial Neural Network (ANN) algorithms. The study shows that ANN provide automatically oil spill detection with error of standard deviation of 0.12 which is lower than Entropy and the Mahalanobis algorithms.
Keywords :
entropy; geophysical image processing; marine pollution; neural nets; oil pollution; synthetic aperture radar; ANN; ENVISAT ASAR data; Mahalanobis algorithm; RADARSAT-1 SAR data; artificial neural network algorithm; automatic oil spill detection; entropy; multisar; Artificial neural networks; Classification algorithms; Conferences; Entropy; Sea measurements; Synthetic aperture radar; Training; Entropy; Mahalanobis neural net work (NN); RADARSAT-1 SAR; oil spill;
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2011 IEEE International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0243-3
DOI :
10.1109/ICSIPA.2011.6144136
