Abstract
Repeat Image Feature Tracking (RIFT) is commonly used to measure glacier surface motion from pairs of images, most often utilizing normalized cross correlation (NCC). The Multiple-Image Multiple-Chip (MIMC) algorithm successfully employed redundant matching (i.e. repeating the matching process over each area using varying combinations of settings) to increase the matching success rate. Due to the large number of repeat calculations, however, the original MIMC algorithm was slow and still prone to failure in areas of high shearing flow. Here we present several major updates to the MIMC algorithm that increase both speed and matching success rate. First, we include additional redundant measurements by swapping the image order and matching direction; a process we term Quadramatching. Second, we utilize a priori ice velocity information to confine the NCC search space through a system we term dynamic linear constraint (DLC), which substantially reduces the computation time and increases the rate of successful matches. Additionally, we develop a novel post-processing algorithm, pseudosmoothing, to determine the most probable displacement. Our tests reveal the complimentary and multiplicative nature of these upgrades in their improvement in overall MIMC performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Geoscience and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
