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Wide swathSynthetic Aperture Radar SAR images acquired over sea areas contain a varietyof information regarding small scale and mesoscale phenomena in the ocean andmarine boundary layer e.g. spills, slicks, surface or internal waves, eddies,oceanic fronts. One of most challenging processing step is to create imageobjects describing these phenomena on SAR images. The most significant problemin the wide swath images is the backscattering trend at the range direction,which results a progressive brightness reduction over images from near to farrange. This reduction affects the detection and classification of sea surfacefeatures on wide swath SAR images and a normalization step is needed in acertain incidence angle for compensating the brightness reduction. The aim ofthe present paper is to investigate the result of image normalization to a setof Wide Swath Mode SAR images. Dark areas were initially detected in SAR imagesusing thresholds, adapted or not. Afterwards, SAR images were normalized and aglobal threshold was calculated for each image. Images were segmented andobjects were created for each dark area. The results were compared to areference dataset created from theoretical modeled values and extracted in aGIS environment. Results clearly indicate that overall accuracy of the detecteddark areas has been increased after normalization. On the contrary, localthresholds were insufficient in producing acceptable results. The proposednormalization can be used as a pre-processing step in image classification.


Synthetic Aperure Radar, Ocean, Normalization, Object Creation

Cite this paper

Topouzelis, K. and Kitsiou, D. 2014 Sea State Primitive Object Creation from SAR Data. International Journal of Geosciences, 5, 1561-1570. doi: 10.4236-ijg.2014.513127.

Author: Konstantinos Topouzelis*, Dimitra Kitsiou



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