TITLE:
Sea State Primitive Object Creation from SAR Data
AUTHORS:
Konstantinos Topouzelis, Dimitra Kitsiou
KEYWORDS:
Synthetic Aperure Radar, Ocean, Normalization, Object Creation
JOURNAL NAME:
International Journal of Geosciences,
Vol.5 No.13,
December
10,
2014
ABSTRACT: Wide swath
Synthetic Aperture Radar (SAR) images acquired over sea areas contain a variety
of information regarding small scale and mesoscale phenomena in the ocean and
marine boundary layer e.g. spills, slicks, surface or internal waves, eddies,
oceanic fronts. One of most challenging processing step is to create image
objects describing these phenomena on SAR images. The most significant problem
in the wide swath images is the backscattering trend at the range direction,
which results a progressive brightness reduction over images from near to far
range. This reduction affects the detection and classification of sea surface
features on wide swath SAR images and a normalization step is needed in a
certain incidence angle for compensating the brightness reduction. The aim of
the present paper is to investigate the result of image normalization to a set
of Wide Swath Mode SAR images. Dark areas were initially detected in SAR images
using thresholds, adapted or not. Afterwards, SAR images were normalized and a
global threshold was calculated for each image. Images were segmented and
objects were created for each dark area. The results were compared to a
reference dataset created from theoretical modeled values and extracted in a
GIS environment. Results clearly indicate that overall accuracy of the detected
dark areas has been increased after normalization. On the contrary, local
thresholds were insufficient in producing acceptable results. The proposed
normalization can be used as a pre-processing step in image classification.