Unsupervised segmentation of hyperspectral images using modified phase correlation


Ertuerk A., Ertuerk S.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol.3, no.4, pp.527-531, 2006 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 3 Issue: 4
  • Publication Date: 2006
  • Doi Number: 10.1109/lgrs.2006.880535
  • Title of Journal : IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
  • Page Numbers: pp.527-531

Abstract

This letter presents hyperspectral image segmentation based on the phase-correlation measure of subsampled hyperspectral data, which is referred to as modified phase correlation. The hyperspectral spectrum of each pixel is initially subsampled to gain, robustness against noise and spatial variability, and phase correlation is applied to determine spectral similarity. Similar and dissimilar pixels are decided according to the peak value of the phase correlation result to determine pixels that fall into the same segments. The approach can be regarded as a region-growing technique. The total number of segments is determined automatically according to the similarity threshold.