Title :
Bi-SOGC: A Graph Matching Approach Based on Bilateral KNN Spatial Orders Around Geometric Centers for Remote Sensing Image Registration
Author :
Ming Zhao ; Bowen An ; Yongpeng Wu ; Changqing Lin
Author_Institution :
Dept. of Logistics Eng., Shanghai Maritime Univ., Shanghai, China
Abstract :
In this letter, Bilateral K Nearest Neighbors Spatial Orders around Geometric Centers (Bi-SOGC) is presented to match feature points for remote sensing images with large affine transformation, similar patterns or multispectral images. In Bi-SOGC, both the bilateral adjacent relations and the spatial angular orders are considered. Bilateral K Nearest Neighbors (BiKNN) descriptors are proposed to describe the adjacent information. The vertices with maximum BiKNN difference are deemed as candidate outliers. The invariant spatial angular orders for affine transformation are used to deal with outliers in pseudo isomorphic structures, geometric centers are taken as the reference points. To increase the correct matching points and eliminate stubborn outliers, a recovery strategy utilizes the addition of fresh inliers to break down the stabilized pseudo graphs of the residual sets. Experimental results demonstrate the superior performance of this algorithm under various conditions for remote sensing images.
Keywords :
affine transforms; graph theory; image matching; image registration; remote sensing; Bi-SOGC; Bilateral K Nearest Neighbors Spatial Orders around Geometric Centers; Bilateral K Nearest Neighbors descriptors; adjacent information; bilateral KNN spatial orders; bilateral adjacent relations; candidate outliers; feature points; fresh inliers; geometric centers; graph matching approach; invariant spatial angular orders; large affine transformation; matching points; maximum BiKNN difference; multispectral images; pseudoisomorphic structures; recovery strategy; reference points; remote sensing image registration; residual sets; stabilized pseudographs; Graph matching; image registration; remote sensing images; spatial orders;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2013.2259612