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Feature Selection Method of Remote Sensing Image Based on Cramer's V Index

A feature selection method and remote sensing image technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problem of low computing efficiency

Inactive Publication Date: 2015-08-12
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, since this method needs to calculate a large number of contingency tables between features in feature selection, the calculation efficiency is not high

Method used

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  • Feature Selection Method of Remote Sensing Image Based on Cramer's V Index
  • Feature Selection Method of Remote Sensing Image Based on Cramer's V Index
  • Feature Selection Method of Remote Sensing Image Based on Cramer's V Index

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Embodiment Construction

[0057] The present invention is based on the high-resolution remote sensing image feature selection method of Cramer's V correlation index, such as figure 1 shown, including the following steps:

[0058] Step 1: Preprocessing the acquired remote sensing images and extracting image features;

[0059] Step 2: Parallel processing of continuous feature discretization based on Cramer's V correlation index;

[0060] Step 3: Parallel processing to obtain the contingency table between two features;

[0061] Step 4: Feature selection based on Cramer's V association index.

[0062] In step 1, the remote sensing image preprocessing process includes the following steps:

[0063] Step 1.1: Perform corresponding preprocessing according to the image quality of the acquired optical remote sensing image data source, including geometric and radiometric correction, image stitching and cropping, image restoration and denoising, or image enhancement and fusion;

[0064] Step 1.2: Extract image...

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Abstract

The invention relates to a high-resolution remote sensing image feature selection method based on a Cramer's V index. The method comprises the following steps of: 1) carrying out pretreatment and image feature extraction on an obtained remote sensing image; 2) carrying out continuous feature discretization parallel processing based on the Cramer's V correlation index; 3) carrying out parallel processing to obtain two contingency tables between two factures; and 4) carrying out feature selection based on the Cramer's V correlation index. The method is good in feature selection effect, high in efficiency and high in applicability, and is capable of efficiently improving the classification accuracy of the remote sensing image. Besides the remote sensing processing, the method can be widely applied to various problems such as pattern classifications of various high-dimensionality and complex type data sets (such as texts, images, medical diagnosis, and genetic data), data mining and visualizing, and the like.

Description

technical field [0001] The invention relates to a feature selection method of high-resolution remote sensing images based on Cramer's V index. Background technique [0002] Because high-resolution images can quickly and accurately obtain detailed information such as landscape structures, geometric shapes, and textures of ground objects, and observe detailed changes in the surface on a small spatial scale, high-resolution images have been widely used in precise monitoring of the surface. It has been widely used in various aspects such as land use update, natural resource and environmental survey, national defense, pipeline, telecommunications, urban planning management, natural disaster monitoring, coastal zone and marine mapping. However, despite the high spatial resolution of high-resolution remote sensing images, there are few imaging spectral channels, which leads to great uncertainty in the spectral information in the images. The main manifestations are: the spectral di...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46G06K9/62
Inventor 吴波曹森茂
Owner FUZHOU UNIV
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