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Method for full-automatic sample selection oriented to classification of remote-sensing images

A remote sensing image and sample technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as improving the degree of automation of classification without special consideration, so as to improve the accuracy and degree of automation, realize automation and precision, and widely representative effect

Inactive Publication Date: 2010-11-24
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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Problems solved by technology

[0006] In the classification methods of remote sensing images, currently available patents and literatures focus on classification algorithms, but there are few studies on the automation and practicability of the classification process, and there is no special consideration for improvement from the stage of sample selection. The degree of automation of classification

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  • Method for full-automatic sample selection oriented to classification of remote-sensing images
  • Method for full-automatic sample selection oriented to classification of remote-sensing images
  • Method for full-automatic sample selection oriented to classification of remote-sensing images

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Embodiment Construction

[0031] figure 1 It is a schematic diagram of the remote sensing image automatic classification method, which includes 6 processing units in total, and the automatic selection of samples composed of C, D, E and F is the key link of the present invention. Before starting the classification, the original remote sensing image needs to be preprocessed (processing unit A), mainly including geometric correction, radiometric correction, etc. The next automatic sample selection process is as follows:

[0032] First of all, it is necessary to determine which categories the current image should be divided into (processing unit B), which is the basic requirement of supervised classification. The present invention adopts the method (as figure 2 shown), the preset category library is equivalent to all the leaf nodes of the standard decision tree, that is, all categories in the preset category library are classified according to the standard decision tree. Although the establishment of a ...

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Abstract

The invention belongs to the technical field of computer-based remote-sensing image information processing and provides a method for full-automatic sample selection oriented to the supervised classification processes of remote-sensing images. The decision tree method is mainly applied to the method of the invention to achieve the integration of geosciences and expert knowledge and hereby carry out the automatic sample selection. The method comprises the following steps: firstly, establishing a standard decision tree according to various indexes, spectra and experiential knowledge; then, automatically pruning and forming a classification decision tree targeted on the current image; and further selecting a sample automatically by using the classification decision tree and introducing membership degree targeted on various requirements for classifiers or specific classification tasks at the same time to automatically adjust the distribution of samples to be selected. Accordingly, the method of the invention can improve the procedure of automatic classification and guarantee the accuracy of sample selection, thus achieving the good effect of classification in cooperation with supervised classification.

Description

technical field [0001] The present invention relates to remote sensing image processing technology and remote sensing image information extraction method, specifically, to remote sensing image classification technology and its core sample automatic selection method, and the present invention is applicable to precise automatic classification of remote sensing images based on various classifier models. Background technique [0002] Remote sensing image classification is the basis of many environmental and socioeconomic applications, so it has always been one of the hotspots in the field of remote sensing research; due to the influence of many factors, remote sensing classification is a complex comprehensive process, so it is also a difficult research point. The existing remote sensing classification methods mainly focus on the application of pattern recognition methods, using the spectral information of remote sensing pixels (or supplemented by spatial information such as textu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 胡晓东夏列钢骆剑承沈占锋郜丽静程熙
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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