Semi-Supervised Hyperspectral Image Segmentation
- J. Li; Dias, J.; A. Plaza;
"Semi-Supervised Hyperspectral Image Segmentation
", Proc
IEEE GRSS Workshop on Hyperspectral Image and Signal Processing
,
Grenoble
,
France
, Vol.
1
, pp.
1
-
4
,
August
,
2009
.
Abstract
This paper introduces a new semi-supervised Bayesian approach to hyperspectral image segmentation. The
algorithm mainly consists of two steps: (a) semi-supervised learning, by using the LORSAL algorithm to infer
the class distributions, followed by (b) segmentation, by inferring the labels from a posterior density built on
the learned class distributions and on a Markov random field. Active label selection is performed. Encouraging
results are presented on real AVIRIS Indiana Pines data set. Comparisons with state-of-the-art algorithms are
also included.
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