Hyperspectral Imaging Remote Sensing

Abstract

A practical and self-contained guide to the principles, techniques, models and tools of imaging spectroscopy. Bringing together material from essential physics and digital signal processing, it covers key topics such as sensor design and calibration, atmospheric inversion and model techniques, and processing and exploitation algorithms. Readers will learn how to apply the main algorithms to practical problems, how to choose the best algorithm for a particular application, and how to process and interpret hyperspectral imaging data. A wealth of additional materials accompany the book online, including example projects and data for students, and problem solutions and viewgraphs for instructors. This is an essential text for senior undergraduate and graduate students looking to learn the fundamentals of imaging spectroscopy, and an invaluable reference for scientists and engineers working in the field.

Sub-pixel detection in hyperspectral imaging with elliptically contoured t-distributed background

“…Hyperspectral imaging has become an increasingly popular tool for remote sensing and scene information retrieval, whether for civil or military needs and in a large number of applications, including analysis of the spectral content of soils, vegetation or minerals, detection of man-made materials or vehicles, to name a few [1,2] . One of the challenges of hyperspectral imaging is to detect a target -whose spectral signature is assumed to be known-within a background whose statistical properties are not fully known [3][4][5] .…”

An Interaction Methodology to Collect and Assess User-Driven Requirements to Define Potential Opportunities of Future Hyperspectral Imaging Sentinel Mission

“…Hyperspectral imaging sensors acquire images characterized by hundreds of contiguous bands with high spectral resolution. The main principles of the hyperspectral imaging rely on the exploitation of light dispersion technologies to split the light beam by using prism optical systems and innovative solutions based on diffraction gratings devices before the detector arrays sensing [33][34][35][36]. The Copernicus Programme is built upon two main pillars:…”

“…In fact, in place of dispersion optical systems, multispectral and super-spectral imaging are achieved by using optical spectral filters applied to the detectors. This different imaging mechanism and the capability of acquiring image with several bands make the design of hyperspectral satellite missions highly demanding [35,36].…”

“…Since the early 1980s, airborne observations have been used to demonstrate the capabilities that hyperspectral remote sensing brings to understanding environment, atmosphere components, and terrestrial and aquatic ecosystems, and to providing information in the field of ecology, agriculture, forest status, oceanography, and geology analyses [33,[36][37][38][39][40], as summarized in Table 1. With reference to the spaceborne configuration, the first satellite-based hyperspectral sensor was Hyperion, which was aboard the NASA EO-1 platform [99].…”

Salient Object Detection on Hyperspectral Images Using Features Learned from Unsupervised Segmentation Task

“…RGB or YCbCr images), hyperspectral imaging systems enable researchers the opportunity to capture data from the observed scenes with high spatial and redundant spectral resolution (both visible and non-visible spectrum to human eye) of the observed scenes from the radiance or reflected light source from objects [2,3,4,5]. These data have been used in many applications (remote sensing [2,6,9], scene analysis or object detection [2,6,7,8,9,10,11], spectral estimation [11,12,13,14], etc. ).…”