Morphological segmentation of hyperspectral images
Image and Video Processing
2020-10-05 v1 Computer Vision and Pattern Recognition
Abstract
The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted to the different hyperspectral functions. Data reduction is performed either by Factor Analysis or by model fitting. Image segmentation is done on different spaces: factor space, parameters space, etc. On all these spaces the spatial/spectral segmentation approach is applied, leading to relevant results on the image.
Cite
@article{arxiv.2010.00853,
title = {Morphological segmentation of hyperspectral images},
author = {Guillaume Noyel and Jesus Angulo and Dominique Jeulin},
journal= {arXiv preprint arXiv:2010.00853},
year = {2020}
}