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Proceedings Paper

An approach for SLAR images denoising based on removing regions with low visual quality for oil spill detection
Author(s): Beatriz Alacid; Pablo Gil
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Paper Abstract

This paper presents an approach to remove SLAR (Side-Looking Airborne Radar) image regions with low visual quality to be used for an automatic detection of oil slicks on a board system. This approach is focused on the detection and labelling of SLAR image regions caused by a poor acquisition from two antennas located on both sides of an aircraft. Thereby, the method distinguishes ineligible regions which are not suitable to be used on the steps of an automatic detection process of oil slicks because they have a high probability of causing false positive results in the detection process. To do this, the method uses a hybrid approach based on edge-based segmentation aided by Gabor filters for texture detection combined with a search algorithm of significant grey-level changes for fitting the boundary lines in each of all the bad regions. Afterwards, a statistical analysis is done to label the set of pixels which should be used for recognition of oil slicks. The results show a successful detection of the ineligible regions and consequently how the image is partitioned in sub-regions of interest in terms of detecting the oil slicks, improving the accuracy and reliability of the oil slick detection.

Paper Details

Date Published: 18 October 2016
PDF: 10 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 1000419 (18 October 2016); doi: 10.1117/12.2239257
Show Author Affiliations
Beatriz Alacid, Univ. de Alicante (Spain)
Pablo Gil, Univ. de Alicante (Spain)


Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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