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Method for semi-supervised detection on changes in remote sensing images

A remote sensing image, change detection technology, applied in image enhancement, image analysis, image data processing and other directions, can solve the problem of slow learning speed, only using original images, etc., to speed up, improve classification accuracy and speed, and speed up learning Effect

Inactive Publication Date: 2016-02-24
HOHAI UNIV
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Problems solved by technology

[0006] The shortcomings of conventional PTSVM for change detection of remote sensing images are: (1) only use the multispectral information of the original image; (2) in semi-supervised learning, each iteration, the set of candidate samples is large, resulting in learning slower

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Embodiment Construction

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0024] figure 1 is a schematic flow chart of an embodiment of the remote sensing image semi-supervised change detection method provided by the present invention, as figure 1 shown, including:

[0025] S101. Obtain the original optical remote sensing image X in two temporal phases 1 and x 2 .

[0026] Among them, X 1 、X 2 These are two high-resolution optical remote sensing images of the same area in different phases.

[0027] S102. For the original optical r...

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Abstract

The present invention discloses a method for semi-supervised detection on changes in remote sensing images. The method comprises: acquiring original optical remote sensing images of two time phases; performing image registration on the original optical remote sensing images; using a histogram adjustment method to perform radiation normalization correction on the remote sensing images having undergone the image registration; calculating spectral angle information according to the remote sensing images having undergone the radiation normalization correction; combining the remote sensing images having undergone the radiation normalization correction with the spectral angle information, and using the combination as input of an FPTSVM; learning by means of an FPTSVM method, and constantly adjusting a classification hyperplane of an SVM until a designated number of learning iterations is reached; and determining a changing area and a non-changing area of the images by using a final classification hyperplane. The method provided by the present invention can increase speed and accuracy of detection on changes.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a semi-supervised change detection method for remote sensing images. Background technique [0002] The change detection of remote sensing images is to identify the state change process of the observed objects or phenomena based on the remote sensing images of different time phases in the same area. It has been widely used in resource management and planning, environmental protection and many other fields, and provides scientific decision-making basis for relevant departments. The current remote sensing image change detection methods mainly include: algebraic method, transformation method, classification comparison method, advanced model method, GIS integration method, visual analysis method and other methods. [0003] Among them, the algebraic method has become one of the most widely used methods in change detection because of its simple operation and eas...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06T5/40
CPCG06T5/40G06T2207/20081G06T2207/10032G06T5/80
Inventor 石爱业高桂荣
Owner HOHAI UNIV
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