A Survey on Fundamental Concepts and Practical Challenges of Hyperspectral images

TL;DR

This survey reviews the fundamental concepts, acquisition, analysis methods, challenges, and applications of hyperspectral images, emphasizing their high-dimensional data and integration with data mining techniques.

Contribution

It provides a comprehensive overview of hyperspectral image processing, including analysis methods, influencing factors, applications, and open issues, serving as a guide for future research.

Findings

Overview of hyperspectral image acquisition and treatment

Analysis of representation spaces and methods

Discussion of open challenges and applications

Abstract

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.