Affine-invariant registration using orthogonal projection matrices for object-based change detection

Contour-based registration provides a feasible approach to object-based change detection with the development of segmentation techniques in remote sensing. In this paper, an affine-invariant registration algorithm based on orthogonal projection matrices is proposed for object-based change detection. First, we extract the objects of interest using segmentation technique and detect the curvature extreme points as feature points in the contour of each object. Then, for each feature point, we construct its descriptor using the orthogonal project matrix of its affine-invariant neighborhood. Finally, object registration is derived through feature point matching based on the descriptor. Experiments of reservoir change detection demonstrate the proposed algorithm is effective in change detection of remote sensing images.