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SAR image change detection method based on mds-srm hybrid cascade

An image change detection and hybrid cascade technology, applied in the field of image processing, can solve the problems such as SRM cannot obtain change detection results, the probability of over-merging errors increases, and achieves the effect of reducing the probability of erroneous merging, improving accuracy, and reasonable sorting.

Active Publication Date: 2019-02-15
XIDIAN UNIV
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Problems solved by technology

However, the SRM algorithm only considers the regional mean difference for static sorting, which will lead to an increase in the probability of over-merging errors, and the final change detection result cannot be obtained with a single use of SRM

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  • SAR image change detection method based on mds-srm hybrid cascade
  • SAR image change detection method based on mds-srm hybrid cascade
  • SAR image change detection method based on mds-srm hybrid cascade

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[0029] specific implementation plan

[0030] The implementation steps and effects of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0031] refer to figure 1 , the implementation steps of the present invention are as follows:

[0032] Step 1, input two single-channel SAR images X of the same region at different times 1 、X 2 , and use the non-local mean algorithm to remove the coherent speckle noise in the two images, and obtain the denoised image I 1 , I 2 .

[0033] (1a) Select the noise image X before the change in the data set 1 ={X 1 (i)|i∈I}, I is the image pixel domain, for any pixel point i in the image, the non-local mean algorithm is used to denoise, and the estimated gray value of the point is obtained as:

[0034]

[0035] Among them, ω(i,j) is the weight value, indicating the similarity between the i-th pixel and the j-th pixel, 0≤ω(i,j)≤1, and Iterate over images X 1 All the pixels in t...

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Abstract

The invention discloses a hybrid cascade change detection method based on MDS-SRM, which mainly solves the problem of inaccurate change detection in the existing SRM algorithm due to static sorting and other factors. The implementation steps are: 1. Input two-phase single-channel SAR images and denoise them respectively; 2. Use the denoised images to construct a logarithmic ratio map and a mean ratio map, and superimpose the two into a dual-channel image. Difference images; 3. Merge the dual-channel difference images to obtain the first merging result; 4. Merge again based on the first merging result to obtain the second merging result; 5. Merge the second merging result The gray average value of each region is sorted in ascending order, and the regions are merged to obtain the final change detection result. The invention can effectively improve the detection accuracy of changing areas in SAR images, and can be used for positioning disaster areas and analyzing urban expansion.

Description

technical field [0001] The invention belongs to the field of image processing, and further relates to a detection method of a two-time-phase image change area, which can be used for the positioning of disaster areas and the analysis of urban expansion. Background technique [0002] With the rapid development of remote sensing technology in recent years, the amount of remote sensing data is increasing day by day, and is widely used in environmental monitoring, atmospheric analysis and urban planning and other fields. Among them, SAR image change detection is applied to military and civilian fields, mainly involving the positioning of natural disaster areas such as floods, fires and earthquakes, the analysis of urban expansion, and the evaluation of strike effects in military applications. Therefore, it is important to study SAR image change detection. significance. [0003] SAR image change detection mainly includes three steps: preprocessing of time phase image, generation ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T5/00G06T5/50
CPCG06T5/50G06T7/0002G06T2207/10044G06T5/70
Inventor 张建龙张羽君高新波周晓鹏
Owner XIDIAN UNIV
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