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Synthetic aperture radar (SAR) image change detection method based on multi-objective evolutionary algorithm based on decomposition (MOEA/D) and fuzzy clustering

A technology for image change detection and multi-objective optimization, which is used in image analysis, image data processing, instrumentation, etc.

Inactive Publication Date: 2014-04-02
XIDIAN UNIV
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Problems solved by technology

[0008] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, and propose a SAR image change detection method based on multi-objective optimization MOEA / D and fuzzy clustering, by taking detail preservation and noise removal as two separate goals for multi-objective Optimized to solve the trade-off between the two essential goals of detail preservation and noise removal in SAR image change detection

Method used

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  • Synthetic aperture radar (SAR) image change detection method based on multi-objective evolutionary algorithm based on decomposition (MOEA/D) and fuzzy clustering
  • Synthetic aperture radar (SAR) image change detection method based on multi-objective evolutionary algorithm based on decomposition (MOEA/D) and fuzzy clustering
  • Synthetic aperture radar (SAR) image change detection method based on multi-objective evolutionary algorithm based on decomposition (MOEA/D) and fuzzy clustering

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Embodiment Construction

[0044] Such as figure 1 as shown,

[0045] The main flowchart step features are:

[0046] Step 101: Two images X of the same region obtained at different times after preprocessing such as registration and geometric correction 1 、X 2 Generate differences using the log ratio method Figure X l , the difference map is obtained according to the calculation formula of the log ratio method as follows:

[0047] X l = | log X 2 X 1 | = | log X 2 - log X 1 |

[0048] where X l is the calculated difference map, X 1 and x 2 are two preprocessed images at different times in the same area, and log is the natural logarithmic operator;

[0049] Step 102: Use the mean filtering metho...

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Abstract

The invention discloses a synthetic aperture radar (SAR) image change detection method based on a multi-objective evolutionary algorithm based on decomposition (MOEA / D) and fuzzy clustering. The problem of balancing two objectives, namely detail maintenance and noise removal in SAR image change detection is solved by a multi-objective optimization method. The method comprises the following steps of (1) generating a difference chart by using a logarithm contrast method for an image to be detected; (2) filtering the difference chart to obtain the denoised difference chart; (3) determining two objective functions according to the two objectives of detail maintenance and noise removal, and combining into a multi-objective optimization problem; (4) obtaining a Pareto front end of the multi-objective problem and a corresponding result chart by using the MOEA / D; (5) selecting a suitable change detection result chart from all results according to a requirement. Compared with a condition that only one solution is obtained by other change detection algorithms, the method has the greatest advantage that the method is used for obtaining an optimal solution set, and a user can select a more suitable solution according to the emphasis on the detail maintenance and the noise removal.

Description

technical field [0001] The invention belongs to the technical field of image processing and evolutionary computing, and relates to a multi-objective optimization algorithm MOEA / D and SAR image change detection, especially a SAR image change detection method based on multi-objective optimization MOEA / D and fuzzy clustering, which can be used for environmental monitoring, Agricultural survey, urban research, disaster relief work and other SAR image change detection related fields. Background technique [0002] In recent years, synthetic aperture radar technology has developed rapidly. The spaceborne synthetic aperture radar system (Synthetic Aperture Radar, SAR) has been observing the earth's surface for several years, and has obtained a large amount of multi-temporal ground observation data. Many remote sensing researches are trying to develop technologies that can make good use of this information, including target extraction, object classification, edge detection, interfero...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 公茂果焦李成王桥马文萍马晶晶李豪雷雨刘嘉
Owner XIDIAN UNIV
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