robust feature matching for slant sar image registration based on differentially constrained ransac

2019 ◽  
Author(s):  
Xin Xiong ◽  
Guowang Jin ◽  
Qing Xu ◽  
Xin Gao ◽  
Ying Cai
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Sar Image

scholarly journals AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

2016 ◽  
Vol XLI-B7 ◽  
pp. 593-600
Author(s):  
C. Xu ◽  
H. G. Sui ◽  
D. R. Li ◽  
K. M. Sun ◽  
J. Y. Liu
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Visual Saliency ◽  
Specific Area ◽  
Image Feature ◽  
Sar Image ◽  
Registration Method ◽  
Adaptive Parameter ◽  
Coarse Registration ◽  
Multi Level

Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM) to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

scholarly journals A Point Pattern Chamfer Registration of Optical and SAR Images Based on Mesh Grids

2018 ◽  
Vol 10 (11) ◽  
pp. 1837 ◽  
Author(s):  
Chu He ◽  
Peizhang Fang ◽  
Dehui Xiong ◽  
Wenwei Wang ◽  
Mingsheng Liao
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Point Pattern ◽  
Sar Image ◽  
Sar Images ◽  
Coarse Registration ◽  
Feature Based ◽  
Mesh Grid ◽  
Coarse To Fine ◽  
Fine Registration

Automatic image registration of optical-to-Synthetic aperture radar (SAR) images is difficult because of the inconsistency of radiometric and geometric properties between the optical image and the SAR image. The intensity-based methods may require many calculations and be ineffective when there are geometric distortions between these two images. The feature-based methods have high requirements on features, and there are certain challenges in feature extraction and matching. A new automatic optical-to-SAR image registration framework is proposed in this paper. First, modified holistically nested edge detection is employed to detect the main contours in both the optical and SAR images. Second, a mesh grid strategy is presented to perform a coarse-to-fine registration. The coarse registration calculates the feature matching and summarizes the preliminary results for the fine registration process. Finally, moving direct linear transformation is introduced to perform a homography warp to alleviate parallax. The experimental results show the effectiveness and accuracy of our proposed method.

scholarly journals AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

2016 ◽  
Vol XLI-B7 ◽  
pp. 593-600 ◽  
Author(s):  
C. Xu ◽  
H. G. Sui ◽  
D. R. Li ◽  
K. M. Sun ◽  
J. Y. Liu
Keyword(s):  
Image Registration ◽  
Feature Matching ◽  
Visual Saliency ◽  
Specific Area ◽  
Image Feature ◽  
Sar Image ◽  
Registration Method ◽  
Adaptive Parameter ◽  
Coarse Registration ◽  
Multi Level

Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM) to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

Multi-view SAR image registration based on feature extraction

2021 ◽  
Author(s):  
JiaZheng Sun ◽  
Hui Wang ◽  
ShiChao Zheng ◽  
ZhaoYang Zeng ◽  
Xiang Chen ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Image Registration ◽  
Sar Image

SAR Image Registration Using Ratio Mutual Information

2012 ◽  
Vol 241-244 ◽  
pp. 2630-2637
Author(s):  
Chun Rong Wei ◽  
Chu He ◽  
Hong Sun
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Reference Image ◽  
Sar Image ◽  
Local Maxima ◽  
Characteristic Quantity ◽  
Registration Algorithm ◽  
Image Registration Algorithm

In order to reduce the noise sensitivity of the SAR (synthetic aperture radar) image registration, a image registration algorithm which basing on the ratio mutual information (RatioMI) is proposed in this paper. Firstly, the ratio images of the reference image and the floating image are gotten by using the ratio operator, and then take the two ratio images as a similar characteristic quantity to construct the similarity measure function which was used in the optimization process of the image registration experiment. The experimental results of the SAR image registration show that the new registration algorithm which based on the RatioMI is effectively in avoiding the local maxima point problems causing by speckle noise.

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