Automatic registration method for medium-resolution remote sensing images of coral reefs with morphological information pairing and constrained iterative fining

Automatic registration of medium-resolution remote sensing images of coral reefs, particularly those without artificial facilities, faces two challenges: difficulty in identifying the same coral reefs in different images and instability of the fine-tuning process. To overcome these challenges, we propose an automatic registration method that combines morphological information pairing with constrained iterative fining. This method comprises three steps. First, the contours of the coral reefs were extracted using level set method. Subsequently, the same coral reefs in the two images were identified and paired based on morphological similarities and relative locations. Finally, iterative fine registration with a constrained strategy was performed by controlling abnormal changes in the geometric center to further improve the registration accuracy for every pair of coral reefs. The proposed automatic registration method was validated using a Landsat5 image acquired on April 15, 2005 and a HJ-1B image acquired on May 4, 2010. Compared with the scale-invariant feature transform (SIFT) method and the SIFT with Random Sample Consensus method, the proposed method showed good performance in the automatic registration of coral reef images.