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SAR image change detection method based on mean shift genetic clustering

A technology of image change detection and genetic clustering, which is applied in the field of synthetic aperture radar image change detection, can solve the problems of high time complexity, lower change detection accuracy, and difficult selection of kernel functions, so as to overcome missed information and suppress background information , the effect of suppressing speckle noise

Active Publication Date: 2015-07-01
XIDIAN UNIV
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Problems solved by technology

However, the disadvantages of this method are that it is difficult to choose a suitable kernel function, and it cannot remove the inherent noise in the SAR image well, and it is sensitive to noise points, which reduces the accuracy of change detection.
However, there are still shortcomings in that it takes a lot of computing time to complete the similarity calculation and search between different pixels, the time complexity is high, and it cannot effectively reduce the change of the region pair between the changed class and the non-changed class. detection results, reducing the accuracy of change detection

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  • SAR image change detection method based on mean shift genetic clustering
  • SAR image change detection method based on mean shift genetic clustering
  • SAR image change detection method based on mean shift genetic clustering

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[0051] The steps of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0052] Refer to attached figure 1 , the concrete steps of the present invention are as follows.

[0053] Step 1, import the image.

[0054] Import two synthetic aperture radar SAR images of the same size acquired at different times in the same area.

[0055] Step 2, Construct difference image.

[0056] Calculate the neighborhood difference image of two synthetic aperture radar SAR images according to the following formula:

[0057] S = 255 - | Σ X 1 ( i , j ) - Σ X 2 ( i ...

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Abstract

The invention provides an SAR image change detection method based on mean shift genetic clustering. The method includes 1, image inputting; 2, differential image construction; 3, mean shift filtering; 4, genetic fuzzy clustering; 5, differential image segmentation; 6, result outputting. The method has the advantages that the influence on synthetic aperture radar (SAR) image change detection results by the region between the change class and non-change class can be reduced effectively, the inherent noise of synthetic aperture radar (SAR) images can be suppressed, the mean shift filtering, fuzzy clustering local optimality and genetic algorithm global optimizing capability are combined, the convergence speed of the algorithm is increased, the detection missing information of detection results is reduced, and the high change detection accuracy is provided.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a synthetic aperture radar (Synthetic Aperture Radar, SAR) image change detection method based on mean shift genetic clustering in the technical field of image change detection. The invention can be applied to the fields of dynamic detection of lake water level, dynamic detection of crop growth state, urban planning, military reconnaissance, etc., to detect changes of ground objects over time. Background technique [0002] SAR image change detection is to analyze multiple SAR images in the same area at different times, and use the gray value of the difference image to divide the image into a changing area and an invariant area, and detect the information that the ground objects in the area change with time. Synthetic aperture radar (SAR) has the characteristics of all-weather and all-weather, is not affected by the weather, and has a certain penetration ability. It...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06T7/00
Inventor 尚荣华焦李成张竹李巧凤马文萍王爽侯彪刘红英屈嵘
Owner XIDIAN UNIV
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