Remote sensing image classification and labeling method based on compound graph conditional random field

A conditional random field and remote sensing image technology, applied in computer components, instruments, calculations, etc., can solve the problems of conditional random field classification performance impact, lack of ability to integrate global interactive information, etc., to achieve enhanced classification and labeling performance, high classification Labeling accuracy, effect of enhanced capabilities

Active Publication Date: 2019-03-22
BEIHANG UNIV
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Problems solved by technology

However, the spatial graph can only fuse the local interaction information of the spatial neighborhood, and lacks the ability to fuse the global interaction information, which affects the classification performance of the conditional random field to a certain extent.

Method used

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  • Remote sensing image classification and labeling method based on compound graph conditional random field
  • Remote sensing image classification and labeling method based on compound graph conditional random field
  • Remote sensing image classification and labeling method based on compound graph conditional random field

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Embodiment Construction

[0035] In the following description, various aspects of the invention will be described. However, for those skilled in the art, only some or all of the structures or procedures of the present invention can be used to implement the present invention. For clarity of explanation, specific data sets and spatial neighborhoods are set forth, but it will be apparent that the invention may be practiced without these specific details. In other instances, well-known features have not been described in detail in order not to obscure the invention.

[0036] Therefore, the present invention provides a method for classifying and labeling remote sensing images based on conditional random fields of composite graphs. In this method, a sparse graph is firstly constructed through a sparse representation, and combined with a spatial graph to construct a composite graph. Sparse representation can find the interaction between samples in the whole sample, so that the newly constructed composite gr...

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Abstract

Aiming at the problem of classification and labeling of remote sensing images, the present invention discloses a method for classification and labeling of remote sensing images based on conditional random fields of composite graphs. Figure; define the correlation potential function and interaction potential function of the conditional random field; optimize the conditional random field model through the quasi-Newton method; infer the test sample through the loop belief propagation algorithm, and obtain its classification and labeling results. In the present invention, a composite graph is constructed by combining a sparse graph capable of expressing global interaction information and a spatial graph capable of expressing local spatial interaction information, which enhances the ability of the graph structure to express data, and further enhances the classification and labeling performance of conditional random fields. It has high classification labeling accuracy.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, and in particular relates to a method for classifying and marking remote sensing images based on conditional random fields of compound graphs. Background technique [0002] Remote sensing technology is the most intuitive, richest and most effective technical means to detect the comprehensive information of land cover. With the rapid development of sensor technology, remote sensing images are gradually showing the characteristics of multi-spectrum, high resolution and large amount of data. The effective acquisition of a large number of comprehensive and information-rich remote sensing images provides complete information resources for the development of related scientific research, but also puts forward higher requirements for remote sensing image processing technology. [0003] In the field of remote sensing, the classification and labeling of remote sensing imag...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/245
Inventor 姜志国张浩鹏吴俊峰尹继豪谢凤英史振威赵丹培罗晓燕
Owner BEIHANG UNIV
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