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Automatic category labeling method for remote sensing images based on author-genre topic model

A remote sensing image and topic model technology, applied in the field of digital images, can solve problems such as the decline in classification accuracy and achieve the effect of improving accuracy

Inactive Publication Date: 2015-11-18
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Application Information

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Problems solved by technology

However, in the case of many regional categories, due to the existence of different types of regions with similar characteristics, the classification accuracy of the ATM-based remote sensing image category labeling method is severely reduced.

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  • Automatic category labeling method for remote sensing images based on author-genre topic model
  • Automatic category labeling method for remote sensing images based on author-genre topic model
  • Automatic category labeling method for remote sensing images based on author-genre topic model

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Embodiment Construction

[0026] The present invention is implemented on the MatlabR2010a experimental platform and mainly includes three steps, which are specifically as follows:

[0027] 1. Training and author-genre theme model generation steps:

[0028] 1) Use the image representation method to represent the training image in the form of visual words, where each training image has a corresponding category label and scene label, and set the visual word w i And author x a , Subject z t And genre c g The total number of and the visual word w i Respectively with the author x a And genre c g The matching relationship. Visual word w i ∈{1,2,...,k}, k is expressed as the number of different visual words obtained according to the training result. Visual words are used to represent the quantized affine invariant regions (some similar blocks) of each image block divided by the training image. Each image block can be mapped into a visual word through the process of clustering. Author x a Indicates the category la...

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Abstract

The invention provides a method for automatically marking a category of a remote sensing image, for increasing category marking precision under the conditions of more area categories and characteristic similarities of different areas. The method for automatically marking the category of the remote sensing image based on an author-genre theme model comprises the following steps: 1) training and generating the author-genre theme model; 2) calculating visual words of the remote sensing image; and 3) judging and marking the category of the remote sensing image: adding the information about genre of the author so as to endow a same image block with author and genre two marking information, estimating so as to obtain the genre information of the image block, and then correcting the estimated author information, thereby effectively increasing the category marking precision.

Description

Technical field [0001] The present invention relates to digital image technology, in particular to remote sensing image intelligent processing technology. Background technique [0002] Remote sensing image annotation is one of the important contents of remote sensing image analysis and understanding. Remote sensing image annotation refers to the allocation of data to remote sensing images in the form of annotations, for example, automatic annotation of commercial areas, residential areas, and farmland in the image. Remote sensing image annotation plays an important role in remote sensing image retrieval system. [0003] The process of automatically classifying remote sensing images is the process of classifying multiple types of targets in the image according to the predefined remote sensing image target classes. [0004] The existing remote sensing image category labeling methods are mainly divided into three categories: (1) machine learning-based methods; (2) system-based methods...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
Inventor 李宏亮罗旺
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA