An Unsupervised Segmentation-based Coder for Multispectral Images

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

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  • M. Cagnazzo

  • L. Cicala

  • G. Poggi

  • G. Scarpa

  • L. Verdoliva

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