BRIFT: A Binary Descriptor for Multi-Modal Image Registration

Using radiation-variation insensitivity feature transform (RIFT) to calculate feature descriptors and perform feature matching on the maximum index map (MIM) is time-consuming. To solve this problem, an algorithm named binary descriptor for RIFT (BRIFT) is proposed. First, the phase consistency of the image is calculated and the MIM is obtained. Then, the feature descriptor is calculated and binarized through fast algorithm on MIM. Finally, the descriptor of each feature point is matched based on Hamming distance. Taking the remote sensing images with various geometric distortions and non-linear radiation distortions as the test data, the BRIFT algorithm is compared with other feature matching algorithms including SIFT, BRISK, BRIEF, RIFT. The comparison result shows that the proposed BRIFT algorithm can save about 80% to 90% of time consumption of feature descriptor evaluation and about 50% of feature matching time consumption with a slight loss of matching accuracy, and achieve fast and robust matching of remote sensing images from different sources.