Registration for SAR and Optical Image via Cross Cumulative Residual Entropy and Ratio Operator

2012 ◽  
Vol 452-453 ◽  
pp. 954-958 ◽  
Author(s):  
Yong Mei Zhang ◽  
Jie Qiong Li
Keyword(s):  
Image Registration ◽  
Optical Image ◽  
Residual Entropy ◽  
Sar Image ◽  
Registration Accuracy ◽  
Sar Images ◽  
Registration Method ◽  
Registration Algorithm ◽  
Cumulative Residual Entropy ◽  
Cumulative Residual

Optical and SAR images have different imaging modes and pixel expression formats, which caused much difficult for image registration. The paper proposes a registration algorithm combined Ratio gradient and Cross Cumulative Residual Entropy (CCRE) aimed at solving the problem of SAR image speckles. Compared with other traditional methods, the experiment results show that the CCRE combined with Ratio operator registration method performs satisfactorily in SAR and optical image registration and provides a significant improvement on the registration accuracy over the other algorithm

scholarly journals REGISTRATION OF OPTICAL AND SAR SATELLITE IMAGES BASED ON GEOMETRIC FEATURE TEMPLATES

2015 ◽  
Vol XL-1-W5 ◽  
pp. 447-452 ◽  
Author(s):  
N. Merkle ◽  
R. Müller ◽  
P. Reinartz
Keyword(s):  
Image Registration ◽  
Optical Image ◽  
Geometric Feature ◽  
Sar Image ◽  
Geometric Accuracy ◽  
Sar Images ◽  
Registration Method ◽  
Sensing Applications ◽  
Optical Images ◽  
High Resolution Radar

Image registration is required for different remote sensing applications, like change detection or image fusion. Since research studies have shown the outstanding absolute geometric accuracy of high resolution radar satellites images like TerraSAR-X, the importance of SAR images as source for geolocation enhancement has increased. Due to this fact, multi-sensor image to image registration of optical and SAR images can be used for the improvement of the absolute geometric processing and accuracy of optical images with TerraSAR-X as reference. In comparison to the common optical and SAR image registration methods the proposed method is a combination of intensity-based and feature-based approaches. The proposed method avoids the direct and often difficult detection of features from the SAR images. SAR-like templates are generated from features detected from the optical image. These templates are used for an intensity-based matching with the SAR image. The results of the matching process are ground control points, which are used for the estimation of translation parameters followed by a subpixel translation of the optical image. The proposed image registration method is tested for two pairs of TerraSAR-X and QuickBird images and one pair of TerraSAR-X andWorldView-2 images of a suburban area. The results show that with the proposed method the geometric accuracy of optical images can be enhanced.

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.

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
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