Region-by-Region Registration Combining Feature-Based and Optical Flow Methods for Remote Sensing Images

Abstract

While geometric registration has been studied in remote sensing community for many decades, successful cases are rare, which register images allowing for local inconsistency deformation caused by topographic relief. Toward this end, a region-by-region registration combining the feature-based and optical flow methods is proposed. The proposed framework establishes on the calculation of pixel-wise displacement and mosaic of displacement fields. Concretely, the initial displacement fields for a pair of images are calculated by the block-weighted projective model and Brox optical flow estimation, respectively in the flat- and complex-terrain regions. The abnormal displacements resulting from the sensitivity of optical flow in the land use or land cover changes, are adaptively detected and corrected by the weighted Taylor expansion. Subsequently, the displacement fields are mosaicked seamlessly for subsequent steps. Experimental results show that the proposed method outperforms comparative algorithms, achieving the highest registration accuracy qualitatively and quantitatively.