Block-and-octave constraint SIFT with multi-thread processing for VHR satellite image matching.

Very high-resolution satellite image matching is a challenging task due to local distortion, repetitive structures, intensity changes and low efficiency. In this letter, a novel approach based on the block and octave constraint scale-invariant feature transform (SIFT) is proposed for very high-resolution satellite image matching. Details regarding multi-thread processing are provided. First, the corresponding matching block is observed using rational function model (RFM) prediction. The RFM prediction can provide a geometric constraint. In each block matching, keypoints are classified with the feature octave. The keypoints are matched in the group with the same feature octave. The block and octave constraint can narrow the keypoints search scope and be helpful for acquiring additional matches. Since blocks are independent, each corresponding block matching is parallelized to realize multi-thread processing with open multi-processing (OpenMP). Experiments are designed to test the matching performance and runtime. The results indicate the effectiveness and efficiency of the proposed approach. [ABSTRACT FROM PUBLISHER]