Non-rigid SAR image registration method based on region similarity and local spatial constraint

A local space and image registration technology, applied in the field of image processing, can solve the problem of poor registration effect of large SAR images

Inactive Publication Date: 2015-06-24
XIDIAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to propose a non-rigid SAR image registration method based on regional similarit

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  • Non-rigid SAR image registration method based on region similarity and local spatial constraint
  • Non-rigid SAR image registration method based on region similarity and local spatial constraint
  • Non-rigid SAR image registration method based on region similarity and local spatial constraint

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[0039] The present invention will be further described below in conjunction with accompanying drawing:

[0040] refer to figure 1 , the implementation steps of the present invention are as follows:

[0041] Step 1, input two images, choose one as the reference image I 1 , take the other as the image to be registered I 2 .

[0042] The two input images are respectively intercepted from two SAR images of different phases acquired by an airborne radar in China.

[0043] Step 2, extract the feature points of the input image, and calculate the local descriptor similarity between the feature points of the reference image and the feature points of the image to be registered.

[0044] 2a) Using the scale-invariant feature transform SIFT method to extract the reference image I 1 and the image to be registered I 2 feature points, the I 1 and I 2 All feature points of are stored in sets R and S respectively;

[0045] 2b) Generate the feature point descriptor des of the reference...

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Abstract

The invention discloses a non-rigid SAR image registration method based on region similarity and local spatial constraint. The problem that an existing rigid registration method is poor in registration effect when applied to a large SAR image is mainly solved. The method comprises the implementation steps that 1, two SAR images are input; 2, feature points of the input images are extracted, and local feature descriptor similarity is calculated; 3, feature point background region similarity is constructed; 4, feature point local spatial constraint conditions are constructed; 5, a matching cost function is constructed according to the step 2, the step 3 and the step 4; 6, iterative optimization is carried out on the matching cost function through a probabilistic relaxation algorithm to obtain the optimal matching point; 7, geometric deformation parameters are obtained according to the optimal matching point, and a registration result is obtained. Compared with the prior art, robustness on speckle noise and feature abnormality points is enhanced, the capacity of simulating non-rigid deformation is improved, the large actual measurement SAR image registration effect is improved, and the method can be used for image fusion and deformation detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image registration method in radar image processing, which can be used for image fusion and change detection. Background technique [0002] Synthetic aperture radar (SAR) system is widely used in military and civilian neighborhoods because of its characteristics of all-day, all-weather, and penetrability. SAR image registration is a key link in the application of SAR images. It is a process of matching and superimposing two or more SAR images of the same scene taken at different times and from different perspectives. Its main purpose is to eliminate or reduce the geometric deformation caused by different imaging conditions between the reference image and the image to be registered, so as to obtain two images with geometric consistency, that is, the best spatial position matching. [0003] Image registration mainly includes two types: rigid registration and non-rigid ...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 吴艳樊建伟李明张庆君王凡张强
Owner XIDIAN UNIV
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