Material Segmentation in Hyperspectral Images with a Spatio-spectral Texture Descriptor

Yu Zhang; Cong Phuoc Huynh; Nariman Habili; King Ngi Ngan

ICASSP 2019accepted0 citations

Material Segmentation in Hyperspectral Images with a Spatio-spectral Texture Descriptor

Yu Zhang, Cong Phuoc Huynh, Nariman Habili, King Ngi Ngan

Abstract

In this paper, we address the problem of ground-based hyperspectral image segmentation by combining pixel-level and region-level classification with a region boundary refinement approach. To this end, we represent the spatio-spectral feature of image regions by a descriptor based on Vector of Locally Aggregated Descriptors (VLAD). Further, the region boundaries are refined by minimizing the total region perimeter. Experimental results on a ground-based hyperspectral image dataset clearly demonstrate the advantage of the proposed method over recent prior works, based on several metrics.

BibTeX

@inproceedings{icassp2019_materialsegmenta,
  title = {Material Segmentation in Hyperspectral Images with a Spatio-spectral Texture Descriptor},
  author = {Yu Zhang and Cong Phuoc Huynh and Nariman Habili and King Ngi Ngan},
  booktitle = {ICASSP 2019},
  year = {2019}
}