Abstract
A new method for the detection of pre-defined boundaries in single-band image data that uses a rotation-variant template matching (RTM) algorithm is presented. This algorithm matches a miniature image of a pre-defined boundary to image data at various orientations. The image pixels that match boundary criteria are reported in output imagery together with the rotation angle of the template. The method is applied to identify boundaries between hydrothermal alteration zones in processed airborne hyperspectral imagery, based on the presence of white mica minerals. Results show that boundaries identified with RTM are relatively free of noise and more coherent than those identified with, for instance, image slicing techniques. Identified boundaries can be used for image segmentation. The output of the RTM algorithm also provides information on the type of boundary, whether it is crisp or gradual. This information can be used to better characterize mineral variation in the alteration halo associated with fossil hydrothermal systems.
Published Version
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 call