  The Remote sensing provides a synoptic view of land by detecting the energy
reflected from Earth's surface. The Hyperspectral images (HSI) use perfect
sensors that extract more than a hundred of images, with more detailed
information than using traditional Multispectral data. In this paper, we aim to
study this aspect of communication in the case of passive reception. First, a
brief overview of acquisition process and treatment of Hyperspectral images is
provided. Then, we explain representation spaces and the various analysis
methods of these images. Furthermore, the factors influencing this analysis are
investigated and some applications, in this area, are presented. Finally, we
explain the relationship between Hyperspectral images and Datamining and we
outline the open issues related to this area. So we consider the case study:
HSI AVIRIS 92AV3C. This study serves as map of route for integrating
classification methods in the higher dimensionality data.
  Keywords-component: Hyperspectral images, Passive Sensing,Classification,
Data mining.
