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Towards Sea Surface Pollution Detection from Visible Band Images
Inna STAINVAS David LOWE
IEICE TRANSACTIONS on Electronics
Publication Date: 2001/12/01
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on New Technologies in Signal Processing for Electromagnetic-wave Sensing and Imaging)
automatic water pollution detection, statistical image segmentation, Gaussian derivative filters, Gabor filters, Gaussian mixture model (GMM),
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This paper presents a novel approach to water pollution detection from remotely sensed low-platform mounted visible band camera images. We examine the feasibility of unsupervised segmentation for slick (oily spills on the water surface) region labelling. Adaptive and non adaptive filtering is combined with density modeling of the obtained textural features. A particular effort is concentrated on the textural feature extraction from raw intensity images using filter banks and adaptive feature extraction from the obtained output coefficients. Segmentation in the extracted feature space is achieved using Gaussian mixture models (GMM).