Paper
22 May 2014 Applying region growing algorithm to hyperspectral image for oil segmentation
Mei-ping Song, Xing-wei Xu, Shuangyang Lu, Wei Xu, Hai-mo Bao
Author Affiliations +
Abstract
Region growing is one of the popular segmentation algorithms for 2-D image, which comes up a continuous interested region. How to extent this method to hyperspectral image processing effectively is a problem needs to be discussed deeply. Here in this paper, three ways of using region growing in hyperspectral scenario are explored to separate oil from sea water. Furthermore, in order to release the influence of sunlight, a modification to growing rule is prompted, considering the property of local region. At last, a normalized ATGP is used to obtain more potential target. The experiment results show that combining unmixing techniques with region growing is better than other methods.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mei-ping Song, Xing-wei Xu, Shuangyang Lu, Wei Xu, and Hai-mo Bao "Applying region growing algorithm to hyperspectral image for oil segmentation", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 912404 (22 May 2014); https://doi.org/10.1117/12.2053333
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Hyperspectral imaging

Detection and tracking algorithms

Image processing algorithms and systems

Image processing

Roentgenium

Surface plasmons

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