1Department of Electronics and Communication Engineering, Institute of Aeronautical Engineering, Dundigal, Hyderabad, Andhra Pradesh, India
2Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Hyderabad, Andhra Pradesh, India
3Department of Electronics and Communication Engineering, Marri Laxman Reddy Institute of Technology and Management, Dundigal, Hyderabad, Andhra Pradesh, India
Online published on 4 November, 2017.
Image registration is a key operation to spatially align two or more images for comparing the difference between them or exploiting complementary information from those images. The main objective regarding automatic registration of satellite images is to obtain an accurate set of tie points and then apply the transformation function which is most suitable to the pair of images to be registered. An efficient method for AIR (Automatic Image Registration) is proposed, which combines image segmentation and scale invariant feature transform (SIFT), complemented by an outlier removal stage. The reference and unregistered images may differ in translation, rotation, and scale and may present distortions. The performance of this method is evaluated through measures such as Nred, RMSall, RMSloo, Pquad, Bad Point Proportion: BPP(r), Scat, Cost Function (φ).
Automatic Image Registration (AIR), Image Segmentation, Optical Images, Scale Invariant Feature Transform (SIFT), Principle Component Analysis (PCA)
