An Unsupervised Segmentation-based Coder for Multispectral Images

  • Cagnazzo M
  • Cicala L
  • Poggi G
 et al. 
  • 3


    Mendeley users who have this article in their library.
  • 0


    Citations of this article.


To fully exploit the capabilities of satellite-borne multi/- hyperspectral sensors, some form of image compression is required. The Gelli-Poggi coder [1], based on segmentation and class-based transform coding, has a very competitive performance, but requires some a-priori knowledge which is not available on-board. In this paper we propose a new version of the Gelli-Poggi coder which is fully unsupervised, and therefore suited for use on-board a satellite, and presents a better performance than the original. Numerical experiments on test multispectral images validate the proposed technique.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • M. Cagnazzo

  • L. Cicala

  • G. Poggi

  • G. Scarpa

  • L. Verdoliva

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free