Information extracting method for remote sensing image continuous target field based on cluster analysis

A technology of cluster analysis and remote sensing images, applied to instruments, character and pattern recognition, computer components, etc., can solve problems such as difficulty in obtaining accuracy, failure to consider continuous target fields, difficulty in automatic information target extraction, etc., to achieve high The effect of accuracy

Inactive Publication Date: 2011-07-06
SATELLITE ENVIRONMENT CENT MINIST OF ENVIRONMENTAL PROTECTION
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Problems solved by technology

However, on the one hand, these classification schemes are difficult to achieve fully automatic information target extraction due to the large amount of manual participation; Because of the uniqueness

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  • Information extracting method for remote sensing image continuous target field based on cluster analysis
  • Information extracting method for remote sensing image continuous target field based on cluster analysis
  • Information extracting method for remote sensing image continuous target field based on cluster analysis

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[0033] In order to make the purpose, content, and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0034] The information extraction method of the remote sensing image continuous target field based on the cluster analysis involved in the technical solution of the present invention comprises the following steps:

[0035] Step S1: Perform feature analysis on the original image data to find out the reference maximum value Max of the regional feature data of the target field to be extracted ref Or refer to the minimum value Min ref ; The reference maximum value and the reference minimum value of the regional feature data are predictive values, which do not necessarily have to be very accurate. This is only a reference for the next step of threshold analysis and processing. Therefore, the reference maximum value can be l...

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Abstract

The invention relates to an information extracting method for a remote sensing image continuous target field based on cluster analysis, and belongs to the technical field of information extraction. The method comprises the following steps: carrying out feature analysis on original image data to find a maximum reference value or a minimum reference value of area character data of the target field to be extracted; carrying out threshold segmentation on the image data according to the maximum reference value or the minimum reference value; carrying out cluster analysis on the image data subjected to the threshold segmentation; rejecting a false target field from a target continuous field obtained by the cluster analysis; and carrying out mask processing on the image subjected to the false target field rejection and an original image to obtain a result image subjected to information extraction. With the technical scheme, the continuous field target can be identified and extracted more automatically; by using the cluster mode, on the basis of a target object, the image features endowed by the continuous field targets in different images are fully considered and the target which is really needed to be identified can be identified and extracted, therefore, compared with the prior art, the information extracting method has higher accuracy.

Description

technical field [0001] The invention belongs to the technical field of information extraction, and in particular relates to an information extraction method for continuous target fields of remote sensing images based on cluster analysis, so as to obtain information such as boundary, range, and distribution of feature fields. Background technique [0002] The common information extraction method of remote sensing images is classification, which can be divided into: supervised classification and unsupervised classification according to whether there is a training area; and common classifiers are based on maximum likelihood method, minimum distance method, vector machine classification, decision tree classification , object-oriented classification, and classification tools for neural networks. However, on the one hand, these classification schemes are difficult to achieve fully automatic information target extraction due to the large amount of manual participation; Because of ...

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
Inventor 王桥熊文成魏斌申文明
Owner SATELLITE ENVIRONMENT CENT MINIST OF ENVIRONMENTAL PROTECTION
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