Object-oriented high-resolution remote-sensing image classification method

A high-resolution, remote sensing image technology, applied in the field of high-resolution remote sensing image classification, can solve the problem of not being able to effectively improve the recognition accuracy

Inactive Publication Date: 2013-01-30
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0005] The technical problem mainly solved by the present invention is to provide an object-oriented high-resolution remote sensing image classification method, which is used to solve the problems that cannot be effe

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Embodiment Construction

[0039] In order to describe the technical content, structural features, achieved goals and effects of the present invention in detail, the following will be described in detail in conjunction with the embodiments and accompanying drawings.

[0040] see figure 1 , this embodiment provides an object-oriented high-resolution remote sensing image classification method, including:

[0041] S1. Perform segmentation processing on the image to be processed to obtain multiple sub-image objects;

[0042] S2. Obtain feature information of the sub-image object;

[0043] S3. Classify the sub-image objects according to the acquired feature information;

[0044]Wherein, the image to be processed is a high-resolution remote sensing image, and the feature information of the sub-image object includes spectral information, shape information and texture information of the sub-image object, wherein the spectral information includes spectral mean value and brightness of each band; the shape infor...

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Abstract

The invention provides an object-oriented high-resolution remote-sensing image classification method. The method comprises the steps of S1, conducting segmentation processing on images to be processed to obtained a plurality of subimage objects; S2, obtaining feature information of subimage objects; and S3, classifying subimage objects according to the obtained feature information, wherein images to be processed are high-resolution remote-sensing images, the feature information of subimage objects comprises spectral information, shape information and texture information of subimage objects. According to the method, on the basis of object-oriented classification, a classification method combining probabilistic latent semantic analysis and a support vector machine is introduced, the problem that 'the same features with different classifications' and 'the same classifications with different features' are not high in identification ratio in the prior art is solved, the classification precision of high-resolution remote-sensing images is greatly improved, advantages of latent semantic analysis (LSA) and advantages of probabilistic latent semantic analysis (PLSA) are combined, and the problems of overfitting and local optimum which are caused by random initialization are effectively solved.

Description

technical field [0001] The invention relates to the field of remote sensing image processing, in particular to an object-oriented high-resolution remote sensing image classification method. Background technique [0002] From the development process of remote sensing image classification technology, it can be seen that classification technology is mainly divided into three levels: (1) pixel-based classification methods, many traditional remote sensing image classification methods belong to this level, and this technology is quite mature; (2) ) The classification method based on objects or primitives is a higher-level classification method developed in the past two decades, and the object-oriented classification method belongs to this level; (3) The classification method based on knowledge is a remote sensing image classification method. A new development trend of technology, its theory is still in the stage of discussion, and its application is not very extensive. [0003] H...

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Application Information

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IPC IPC(8): G06K9/62G06K9/54
Inventor 程建刘婷何吟付莉
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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