The Hit-or-Miss transform (HMT) is a common tool in Mathematical Morphology (MM) used in template matching and object detection and subsequent classification applications. The HMT probes a query image with a pair of structuring elements (SEs) which are designed to detect specific objects of interest. The relative size of hyperspectral image data in particular provides a wealth of information on a scene however, it also makes object detection via a HMT a computationally expensive process. We aim to solve this problem through employing both spatial and spectral dimensionality reduction (DR) techniques to transform a hyperspectral image and its associated SEs designed for the HMT into a reduced space.
|Number of pages||2|
|Publication status||Published - 10 Oct 2018|
|Event||Hyperspectral Imaging Applications (HSI) 2018 - |
Duration: 10 Oct 2018 → 11 Oct 2018
|Conference||Hyperspectral Imaging Applications (HSI) 2018|
|Period||10/10/18 → 11/10/18|
- Hit-or-Miss Transform
- Mathematical Morphology
- structuring elements
- hyperspectral image data
Macfarlane, F., Murray, P., Marshall, S., & White, H. (2018). A fast hyperspectral hit-or-miss transform with integrated projection-based dimensionality reduction. Paper presented at Hyperspectral Imaging Applications (HSI) 2018, .