Mendeley
TY  _  JOUR
ID  -  2021083124200
TI  -   Remote Sensing Image Registration based on a Geometrical Model Matching
JO  -  Journal of Information Systems and Telecommunication (JIST) 
JA  -  ES
LA  -  en
SN  -  2322-1437
AU  -  Hossein-Nejad Zahra
AU  -  Agahi Hamed
AU  -  Mahmoodzadeh Azar
AD  -  Islamic Azad University Shiraz
AD  -  Islamic Azad University Shiraz
AD  -  Islamic Azad University Shiraz
Y1  -  2021
PY  -  2021
VL  -  0
IS  -  
SP  -  41
EP  -  50
KW  -  SIFT
KW  -   Matching Method
KW  -   Remote Sensing Image Registration
KW  -   Transformation Model
DO  -  
N2  -  Remote sensing image registration is the method of aligning two images from the same scene taken under different imaging circumstances containing different times, angles, or sensors. Scale-invariant feature transform (SIFT) is one of the most common matching methods previously used in the remote sensing image registration. The defects of SIFT are the large number of mismatches and high execution time due to the high dimensions of classical SIFT descriptor. These drawbacks reduce the efficiency of the SIFT algorithm. To enhance the performance of the remote sensing image registration, this paper proposes an approach consisting of three different steps. At first, the keypoints of both reference and second images are extracted using SIFT algorithm. Then, to increase the speed of the algorithm and accuracy of the matching, the SIFT descriptor with the vector length of 64 is used for keypoints description. Finally, a new method has been proposed for the image matching. The proposed matching method is based on calculating the distances of keypoints and their transformed points. Simulation results of applying the proposed method to some standard databases demonstrated the superiority of this approach compared with some other existing methods, according to the root mean square error (RMSE), precision and running time criteria.
UR  - rimag.ir/en/Article/24200
L1  - rimag.ir/en/Article/Download/24200
ER  -  
