A fast hyperspectral hit-or-miss transform with integrated projection-based dimensionality reduction

Tools

Macfarlane, Fraser and Murray, Paul and Marshall, Stephen and White, Henry (2018) A fast hyperspectral hit-or-miss transform with integrated projection-based dimensionality reduction. In: Hyperspectral Imaging Applications (HSI) 2018, 2018-10-10 - 2018-10-11.

[thumbnail of Macfarlane-etal-HSI-2018-A-fast-hyperspectral-hit-or-miss-transform-with-integrated-projection]
Preview
 Text. Filename: Macfarlane_etal_HSI_2018_A_fast_hyperspectral_hit_or_miss_transform_with_integrated_projection.pdf
Accepted Author Manuscript
Download (3MB)| Preview

Abstract

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.

ORCID iDs

Macfarlane, Fraser ORCID logoORCID: https://orcid.org/0000-0002-7411-1446, Murray, Paul ORCID logoORCID: https://orcid.org/0000-0002-6980-9276, Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628 and White, Henry;
CORE (COnnecting REpositories)