High spectral oil overflow image classification method based on Fuzzy ARTMAP neural network

A hyperspectral oil spill and image classification technology, which is applied in the field of hyperspectral oil spill image classification based on the Fuzzy ARTMAP neural network, can solve the problems of classification results misclassification, missing classification, and low effect of remote sensing classification accuracy, and improve the accuracy , Improve the effect of classification ability

Inactive Publication Date: 2016-08-10
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

While the above method has its own advantages, it also has unsatisfactory classification effects on the same spectrum of different objects, the same object with different spectra, and mixed pixels. The classification results often have the s

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  • High spectral oil overflow image classification method based on Fuzzy ARTMAP neural network
  • High spectral oil overflow image classification method based on Fuzzy ARTMAP neural network
  • High spectral oil overflow image classification method based on Fuzzy ARTMAP neural network

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[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0023] refer to Figure 1-5 , a kind of hyperspectral oil spill image classification method based on Fuzzy ARTMAP neural network of the present invention is characterized in that, comprises the following steps:

[0024] (a) Preprocessing the original image, selecting the optimal band;

[0025] (b) selecting an area of ​​interest;

[0026] (c) Establish the Fuzzy ARTMAP neural network model and determine the initial parameters;

[0027] (d) Use the feature v...

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Abstract

The invention discloses a high spectral oil overflow image classification method based on a Fuzzy ARTMAP neural network. Based on combination between the Fuzzy ARTMAP neural network and a classifier, the high spectral oil overflow image classification method has advantages of improving classification precision of the high spectral image, facilitating more accurate oil overflow detection, sufficiently exerting an advantage of high studying capability of the Fuzzy ARTMAP neural network as the classifier, improving oil overflow remote sensing image classification precision and settling a problem of outdated traditional classifier for oil overflow detection.

Description

technical field [0001] The invention relates to the application of remote sensing image classification technology in the field of marine oil spill detection, in particular to a hyperspectral oil spill image classification method based on FuzzyARTMAP neural network. Background technique [0002] With the rapid development of global marine transportation and offshore oil exploitation, marine oil spill accidents occur frequently, and oil spill monitoring has become the primary issue for quickly and effectively dealing with oil spill accidents. premise. Marine oil spill detection methods include artificial sea, sea buoys and remote sensing methods. The first two cost a lot of money. Remote sensing methods can greatly save costs by obtaining satellite data or aircraft cruises cheaply or even free of charge. Therefore, remote sensing technology is an effective means of marine oil spill detection. According to different data sources, remote sensing oil spill detection methods can ...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2148G06F18/24
Inventor 宋冬梅陈伟民张雅洁马毅任广波崔建勇吴会胜沈晨
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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