The impact of multivariate quasi-flat zones on the morphological description of hyperspectral images

No Thumbnail Available

Date

2014

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis Ltd

Research Projects

Organizational Units

Journal Issue

Abstract

Quasi-flat zones are powerful morphological image simplification tools capable of producing unique image partitions at multiple scales. In this paper we investigate their impact on the morphological description of hyperspectral images and, specifically, whether they can improve classification performance when used for preprocessing. In particular, we employ them in order to group spatially adjacent pixels according to spectral criteria, prior to the computation of extended morphological profiles. Moreover, we explore both marginal quasi-flat zones and recent multivariate extensions using well-known vector orderings. The method studied is tested with multiple hyperspectral images, where it leads consistently to improvements in classification performance.

Description

Aptoula, Erchan/0000-0001-6168-2883

Keywords

[No Keyword Available]

Turkish CoHE Thesis Center URL

Citation

9

WoS Q

Q2

Scopus Q

Q1

Source

Volume

35

Issue

10

Start Page

3482

End Page

3498