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Fuzzy clustering analysis method for detecting synthetic aperture radar (SAR) image changes based on non-local means

A technology of image change detection and fuzzy cluster analysis, applied in the field of difference map analysis, can solve the problems of high detection error rate and sensitivity of difference map to noise, so as to improve the denoising efficiency, reduce the false detection rate, and achieve the best change detection results. Effect

Inactive Publication Date: 2015-06-03
XIDIAN UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to: use the improved fuzzy C-means clustering to divide the difference information map in the SAR image change detection into two types: changed / unchanged, to overcome the sensitivity of the existing difference map analysis method to the noise in the difference map, and to reduce the detection error rate. higher defect

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  • Fuzzy clustering analysis method for detecting synthetic aperture radar (SAR) image changes based on non-local means
  • Fuzzy clustering analysis method for detecting synthetic aperture radar (SAR) image changes based on non-local means
  • Fuzzy clustering analysis method for detecting synthetic aperture radar (SAR) image changes based on non-local means

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Embodiment 1

[0039] The present invention is a kind of SAR image change detection fuzzy cluster analysis method based on non-local mean value, see figure 1 , first construct a difference map for two SAR images of the same region at different times, and then correct the pixel values ​​according to the similarity index in the global fast fuzzy C-means clustering (FGFCM) algorithm, and obtain the pixel value matrix considering the local spatial information, Then, non-local mean filtering is performed on the difference map to obtain the non-local filtered pixel value matrix, and then the local spatial information matrix and the non-local information matrix are weighted and combined to generate a complete pixel value matrix, and finally the FGFCM algorithm is used to aggregate it. Class, and then generate a change detection result map through the clustering result, and complete the final detection of the change area in the two SAR images. The specific implementation steps of the fuzzy clustering...

Embodiment 2

[0060] The fuzzy clustering analysis method for SAR image change detection based on non-local means is the same as in embodiment 1, with reference to figure 1 , adopt the present invention to obtain the difference map and the reference map of two synthetic aperture radar (SAR) images at different times in the Bern region to simulate in this example, and carry out difference information map analysis, and the realization steps are as follows:

[0061] Step 1. Obtain two synthetic aperture radar (SAR) images at different times in the Bern area, and filter and denoise the two SAR images, perform radiometric correction and geometric registration preprocessing, and the preprocessed two SAR images are SAR image x 1 , SAR image X 2 , where the image X obtained after preprocessing 1 Such as figure 2 as shown in (a), figure 2 (a) is the geomorphic information of the Bern area in April 1999, the image X obtained after preprocessing 2 Such as figure 2 as shown in (b), figure 2 ...

Embodiment 3

[0074] The SAR image change detection fuzzy clustering analysis method based on non-local means is the same as that in Embodiment 1-2,

[0075] Effect of the present invention can be further illustrated by following simulation:

[0076] 1. Simulation parameters

[0077] For the experimental simulation graph group with reference graphs, quantitative change detection results can be analyzed. The main evaluation indicators are:

[0078] ①Number of missing detections: Count the number of pixels in the changed area in the experimental result image, compare it with the number of pixels in the changed area in the reference image, and count the number of pixels that have changed in the reference image but are detected as unchanged in the experimental result image , called the missed detection number;

[0079] ②Number of false detections: Count the number of pixels in the unchanged area in the experimental result image, compare it with the number of pixels in the unchanged area in th...

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Abstract

The invention discloses a fuzzy clustering analysis method for detecting SAR image changes based on non-local means. The method is implemented through the processes of inputting a difference chart composed of two SAR images in a same region at different times; correcting pixels of the difference chart according to similarity measure indexes in a fast global fuzzy C-Means clustering (FGFCM) algorithm to obtain a local spatial information pixel matrix; performing non-local mean processing on the difference chart to generate a pixel matrix of non-local filtering waves; weighting and summing up the two matrixes and generating a complete pixel matrix; clustering the complete pixel matrix through the FGFCM algorithm to generate a change detection binary result image and complete the change detection of the two SAR images integrally. According to the fuzzy clustering analysis method for detecting SAR image changes based on non-local means, local spatial information and non-local mean information of images are considered simultaneously and combined organically, so that noise influences are overcome effectively and image details are kept in an image analysis clustering process, and accurate difference chart analysis results are obtained.

Description

technical field [0001] The invention belongs to the technical field of SAR image change detection and relates to a difference map analysis technology in SAR image change detection. Specifically, a fuzzy clustering analysis method for SAR image change detection based on non-local mean is proposed, which is used to classify and analyze the difference map in SAR image change detection, and overcome the high error rate of the original method for changing area detection. To improve the detection accuracy and speed in SAR image change detection. Background technique [0002] With the rapid development of synthetic aperture radar (SAR) technology, SAR system can acquire image data all-weather and all-weather, and it is a better image source for change detection. SAR image change detection is to compare and analyze two SAR images in different periods in the same area, and obtain the required ground object change information according to the difference between the images. SAR image...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/54G06T7/00G01S13/90
Inventor 公茂果焦李成陈默马晶晶贾萌李瑜翟路王爽王桂婷马文萍
Owner XIDIAN UNIV
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