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Remote sensing character optimization algorithm for improving mRMR (min-redundancy max-relevance) algorithm

An algorithm and remote sensing technology, applied in computing, computer parts, instruments, etc., can solve the problem of less discussion, achieve low data requirements, high computing efficiency, and simple principles

Inactive Publication Date: 2015-07-22
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, from the perspective of content, these patents do not specifically involve the optimization method of multi-features, but only a simple application, and there are few related discussions

Method used

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  • Remote sensing character optimization algorithm for improving mRMR (min-redundancy max-relevance) algorithm
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  • Remote sensing character optimization algorithm for improving mRMR (min-redundancy max-relevance) algorithm

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Embodiment Construction

[0031] figure 1 The main realization idea of ​​the present invention is illustrated. In the process of high-resolution remote sensing image processing and classification, it is necessary to use remote sensing multi-scale segmentation algorithms to achieve image segmentation (methods can choose mean shift, watershed, multi-resolution, SLIC, etc.), and further perform segmentation on the segmented primitive objects. Multi-feature calculation, and then according to the characteristics of different objects, the land category of the object is judged, and the classification process of the land parcel object is completed. Since there are many features that can be calculated on the plot, such as figure 2 In the list of commonly used feature calculations shown, generally in the calculation of primitive features, object spectral features, texture features, and shape features are mostly used, followed by spatial relationship features between multiple objects. Different features will p...

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Abstract

The invention provides a remote sensing character optimization algorithm for improving an mRMR (min-redundancy max-relevance) algorithm. In an object-oriented high-resolution remote sensing ground surface classifying process, a certain algorithm needs to be used for dividing a high-resolution remote sensing image so as to obtain a series of primitive objects, various features of the primitive objects are calculated, properties of the primitive objects are determined according to the features of the different primitive objects, and a ground block object classifying process is finished. Because ground block features are numerous, the feature which is the most effective on determination of ground blocks needs to be selected from the various features, and the process is a feature optimization process. On the basis of a correlation theory of mutual information in an information theory, three methods comprising binary discretization, histograms and F statistics are used for implementing a calculation process of the mRMR algorithm, and the feature optimization process is implemented by the mRMR algorithm. The feature optimization process can be implemented efficiently. Moreover, the remote sensing character optimization algorithm can be widely used for applications such as similar feature optimization and feature validity check and evaluation of certain ground object types.

Description

technical field [0001] The invention relates to a feature optimization algorithm applied between feature calculation and image classification in the field of remote sensing digital image processing. Specifically, in the process of remote sensing image processing and information extraction, it is necessary to perform object feature calculation after remote sensing image segmentation , to selectively optimize some of the features, so as to realize the image classification process more efficiently while maintaining the same accuracy. The present invention is applicable to the image classification process with large amount of data or more complex, especially for the optimal process after calculating a large number of features. Background technique [0002] Remote sensing image classification technology is one of the key technologies in remote sensing digital image processing. It has been widely used in many fields such as agriculture and military affairs, and has played an impor...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2163G06F18/241G06F18/2415
Inventor 沈占锋程希萌骆剑承夏列钢
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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