Skip to main content
padlock icon - secure page this page is secure

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

Buy Article:

$60.00 + tax (Refund Policy)

Quasi-fl at 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.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: Computer Engineering Department, Okan University, Istanbul, Turkey

Publication date: May 19, 2014

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more