AN UNSUPERVISED SEGMENTATION-BASED CODER FOR MULTISPECTRAL IMAGES (WedAmPO3)

Author(s) : Marco Cagnazzo (Università di Napoli - Federico II, Italy) Luca Cicala (Università di Napoli - Federico II, Italy) Giovanni Poggi (Università di Napoli - Federico II, Italy) Luisa Verdoliva (Università di Napoli - Federico II, Italy) Giuseppe Scarpa (Università di Napoli - Federico II, Italy)

Abstract : To fully exploit the capabilities of satellite-borne multi-hyperspectral sensors, some form of image compression is required. The Gelli-Poggi coder, 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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