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.

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

To solve the mis-clusters caused by the traditional information cut algorithm when it is applied to segment images with gray changes, modified information cut in wavelet domain (W-MIC) algorithm is proposed. First, using the gray relevance and space relevance between image pixels, a modified information cut (MIC) is presented, which utilizes a new Parzen windowing function to evaluate probability density functions, and reduces the effect of gray changes to image segmentation; further, considering the difficulties of selecting the optimal parameter in MIC, the proposed W-MIC can reduce the complexity of parameter selection via the smoothing role of wavelet, and improve segmentation results by fusing low frequency information and high frequency information derived from undecimated wavelet decomposition. Segmentation experiments demonstrate that it effectively decreases the influence of parameters selection, and it can not only avoid the mis-clusters caused by gray changes, but also keep image edges.

Image segmentation based on modified information cut in wavelet domain

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Image segmentation based on modified information cut in wavelet domain