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high-resolution image house information rapid supervision and identification method based on BFD-IGA-SVM model

A high-resolution, image technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of many original features, low precision, no use of different types of feature selection and object-oriented methods, etc.

Inactive Publication Date: 2019-10-08
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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Problems solved by technology

[0004] Previous research mainly focused on a single feature extraction method and pixel-based analysis, and required input of more original features, did not take advantage of different categories of feature selection and object-oriented methods, and did not fully consider the classifier parameter optimization problem
The efficiency is slow and the accuracy is not high

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  • high-resolution image house information rapid supervision and identification method based on BFD-IGA-SVM model
  • high-resolution image house information rapid supervision and identification method based on BFD-IGA-SVM model
  • high-resolution image house information rapid supervision and identification method based on BFD-IGA-SVM model

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Embodiment Construction

[0118] Such as figure 1 As shown, it represents the overall process of house extraction under the feature optimization framework of the present invention, which is mainly divided into 3 major aspects:

[0119] The first is to construct high-resolution remote sensing image objects through multi-scale segmentation. Image objects are the carriers of features and knowledge expression, and accurate construction of image objects is the basis for subsequent target recognition;

[0120] Second, feature selection, by combining the ReliefF algorithm, genetic algorithm and support vector machine model, optimize and optimize the features to form the optimal feature subset of the house;

[0121] Third, using a support vector machine model, house information extraction and recognition are performed on the above preferred subset of features, and its sensitivity is compared with related methods.

[0122] A fast supervised recognition method for high-resolution image building information base...

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Abstract

The invention discloses a high-resolution image house information rapid supervision and identification method based on a BFD-IGA-SVM model. The method is characterized by on the basis of a house building target feature system, constructing an object of a high-resolution remote sensing image through multi-scale segmentation, wherein the image object is a carrier of the feature and knowledge expression, and the accurate construction of the image object is the basis of the subsequent target recognition; extracting the feature variables, and optimizing the features by combining a ReliefF algorithm, a genetic algorithm and a support vector machine model to form a house optimal feature subset; carrying out house information extraction and identification on the optimal feature subset of the house, and comparing the sensitivity of the optimal feature subset of the house with that of a related method. The method is higher in precision and very good in robustness, greatly improves the house extraction efficiency, achieves the quick extraction of the post-disaster onsite house information, is very good in application value, and achieves the important information support for the post-disasterreconstruction and quick rescue.

Description

technical field [0001] The invention relates to the technical field of remote sensing monitoring. Specifically, it is based on the BFD-IGA-SVM model for fast supervised recognition of high-resolution image building information. Background technique [0002] At present, with the rapid development of space technology and sensor technology, high-resolution remote sensing data has increased massively, and has been widely used in fields such as land cover mapping and monitoring, object recognition and information extraction. In terms of image interpretation methods, It is mainly based on pixel and object interpretation methods. [0003] Among them, the pixel-based method cannot meet the needs of information extraction with the increase of image spatial resolution, while the object-oriented method considers the spectral, geometric, texture and topological relations of image objects, which makes it possible to utilize contextual semantic information. However, the selection of fea...

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/62
CPCG06V20/194G06V20/176G06V10/267G06F18/2411
Inventor 周艺王福涛张锐王世新
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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