REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES
Asker, M., Abu —ElNasr, O., Shabana, B., Elmougy, S. (2016). REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES. EKB Journal Management System, 16(3), 47-66. doi: 10.21608/ijicis.2016.19838
M. Asker; O. Abu —ElNasr; B. Shabana; S. Elmougy. "REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES". EKB Journal Management System, 16, 3, 2016, 47-66. doi: 10.21608/ijicis.2016.19838
Asker, M., Abu —ElNasr, O., Shabana, B., Elmougy, S. (2016). 'REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES', EKB Journal Management System, 16(3), pp. 47-66. doi: 10.21608/ijicis.2016.19838
Asker, M., Abu —ElNasr, O., Shabana, B., Elmougy, S. REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES. EKB Journal Management System, 2016; 16(3): 47-66. doi: 10.21608/ijicis.2016.19838

REGISTRATION OF REMOTE SENSING IMAGES BASED ON FEATURE FUSION TECHNIQUES

International Journal of Intelligent Computing and Information Sciences
Article 4, Volume 16, Issue 3, July 2016, Page 47-66  XML PDF (3.58 MB)
Document Type: Original Article
DOI: 10.21608/ijicis.2016.19838
View on SCiNiTO View on SCiNiTO
Authors
M. Asker1; O. Abu —ElNasr1; B. Shabana2; S. Elmougy3
1Faculty of Computers and Information, Mansoura University, Egypt
2Faculty of Computers and and Computer Science, Information, Mansoura-Egypt.
3Faculty of Computers and and Information
Abstract
Geometric correction is used to correct the registration errors in remotely sensed images. These images are often compared to ground control points (GCPs) either by using an accurate map (image to map) or using another geo-referenced image (image to image) and then resampled. Accordingly, the exact locations and the appropriate pixel values can be calculated in more accurate, time-wise and effortless manner. In the traditional methods, the GCPs are manually selected and then the transformation models are applied which yield time consuming and less accurate processes. The objective of this work is to develop an automatic approach for image registration based on another geo-referenced image using five feature extraction models. They are Scale Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), Discrete Wavelet Transforms (DWT), (SIFT & DWT), and (SURF & DWT). The GCPs were selected based on the least-squares adjustments as the basis for improving the spatial accuracy of all the linking points in both images. The obtained results showed that models have higher accuracy in image registration with Root Mean Square Error (RMSE) less than 0.5. The developed automated image registration method provides more accurate results and saves time, money and effort.
Keywords
Geometric correction; GCPs; SIFT; SURF; DWT
Statistics
Article View: 152
PDF Download: 208