A Hybrid Registration Approach of Remote Sensing Images for Land Consolidation

Significant developments in the field of remote sensing have widened the application fields of remote sensing. One of the application fields is a land consolidation project. Multi-temporal and/or multi-sensor remote sensing provides a unique tool to track land utilization dynamics but requires precise registration of thousands of satellite images. However, automatic registration between remote sensing images is a challenging problem due to the different geometric distortion within the images, the illumination variation and varying resolution. To address this problem, we propose a hybrid automatic image registration scheme (technique), which combines Phase Correlation (PC) method and SIFT descriptor registration together. Based on the specific characteristic of the remote sensing imagery, we apply a Phase Correlation (PC) method first to coarsely proregister the input image to the reference image. Then, a fine-scale registration process based on the scale invariant feature transform (SIFT) method is constructed. Experiments with Quickbird, CBERS-1remote-sensing images of the Land Consolidation area in Beijing demonstrate that the proposed hybrid method is fully automatic and fast. Moreover, the registration accuracy is higher than traditional methods.