New region feature descriptor-based image registration method

2012 ◽  
Author(s):  
Francis Bowen ◽  
Eliza Du ◽  
Jianghai Hu
Keyword(s):  
Image Registration ◽  
Feature Descriptor ◽  
Registration Method ◽  
Region Feature

scholarly journals An Image Registration Method Using Deep Residual Network Features for Multisource High-Resolution Remote Sensing Images

2021 ◽  
Vol 13 (17) ◽  
pp. 3425
Author(s):  
Xin Zhao ◽  
Hui Li ◽  
Ping Wang ◽  
Linhai Jing
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Image Registration ◽  
Feature Descriptor ◽  
Remote Sensing Images ◽  
Residual Network ◽  
Scale Invariant ◽  
Registration Method ◽  
Sensing Applications ◽  
Feature Based

Accurate registration for multisource high-resolution remote sensing images is an essential step for various remote sensing applications. Due to the complexity of the feature and texture information of high-resolution remote sensing images, especially for images covering earthquake disasters, feature-based image registration methods need a more helpful feature descriptor to improve the accuracy. However, traditional image registration methods that only use local features at low levels have difficulty representing the features of the matching points. To improve the accuracy of matching features for multisource high-resolution remote sensing images, an image registration method based on a deep residual network (ResNet) and scale-invariant feature transform (SIFT) was proposed. It used the fusion of SIFT features and ResNet features on the basis of the traditional algorithm to achieve image registration. The proposed method consists of two parts: model construction and training and image registration using a combination of SIFT and ResNet34 features. First, a registration sample set constructed from high-resolution satellite remote sensing images was used to fine-tune the network to obtain the ResNet model. Then, for the image to be registered, the Shi_Tomas algorithm and the combination of SIFT and ResNet features were used for feature extraction to complete the image registration. Considering the difference in image sizes and scenes, five pairs of images were used to conduct experiments to verify the effectiveness of the method in different practical applications. The experimental results showed that the proposed method can achieve higher accuracies and more tie points than traditional feature-based methods.

scholarly journals An Infrared-Visible Image Registration Method Based on the Constrained Point Feature

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1188
Author(s):  
Qingqing Li ◽  
Guangliang Han ◽  
Peixun Liu ◽  
Hang Yang ◽  
Huiyuan Luo ◽  
...  
Keyword(s):  
Image Registration ◽  
Evaluation Method ◽  
Detection Algorithm ◽  
Feature Descriptor ◽  
Registration Accuracy ◽  
Visible Image ◽  
Registration Method ◽  
Visible Images ◽  
Image Pairs ◽  
Point Feature

It is difficult to find correct correspondences for infrared and visible image registration because of different imaging principles. Traditional registration methods based on the point feature require designing the complicated feature descriptor and eliminate mismatched points, which results in unsatisfactory precision and much calculation time. To tackle these problems, this paper presents an artful method based on constrained point features to align infrared and visible images. The proposed method principally contains three steps. First, constrained point features are extracted by employing an object detection algorithm, which avoids constructing the complex feature descriptor and introduces the senior semantic information to improve the registration accuracy. Then, the left value rule (LV-rule) is designed to match constrained points strictly without the deletion of mismatched and redundant points. Finally, the affine transformation matrix is calculated according to matched point pairs. Moreover, this paper presents an evaluation method to automatically estimate registration accuracy. The proposed method is tested on a public dataset. Among all tested infrared-visible image pairs, registration results demonstrate that the proposed framework outperforms five state-of-the-art registration algorithms in terms of accuracy, speed, and robustness.

Image registration method based on multiresolution for dual-energy subtraction radiography

2012 ◽  
Author(s):  
Takahiro Kawamura ◽  
Norihiro Omae ◽  
Masahiko Yamada ◽  
Wataru Ito ◽  
Kiyosumi Kawamoto ◽  
...  
Keyword(s):  
Image Registration ◽  
Dual Energy ◽  
Registration Method ◽  
Energy Subtraction

scholarly journals Feature-Area Optimization: A Novel SAR Image Registration Method

2016 ◽  
Vol 13 (2) ◽  
pp. 242-246 ◽  
Author(s):  
Fuqiang Liu ◽  
Fukun Bi ◽  
Liang Chen ◽  
Hao Shi ◽  
Wei Liu
Keyword(s):  
Image Registration ◽  
Sar Image ◽  
Registration Method ◽  
Area Optimization
Sign in / Sign up

Export Citation Format

Share Document