Imaging Spectroscopy for Scene Analysis / by Antonio Robles-Kelly, Cong Phuoc Huynh.

Format:

Book

Author/Creator:

Robles-Kelly, Antonio A., author.

Huynh, Cong Phuoc, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Advances in computer vision and pattern recognition 2191-6586

Advances in Computer Vision and Pattern Recognition, 2191-6586

Language:

English

Subjects (All):

Pattern perception.

Optical data processing.

Pattern Recognition.

Image Processing and Computer Vision.

Local Subjects:

Pattern Recognition.

Image Processing and Computer Vision.

Physical Description:

1 online resource (XVIII, 270 pages).

Edition:

First edition 2013.

Contained In:

Springer eBooks

Place of Publication:

London : Springer London : Imprint: Springer, 2013.

System Details:

text file PDF

Summary:

In contrast with trichromatic image sensors, imaging spectroscopy can capture the properties of the materials in a scene. This implies that scene analysis using imaging spectroscopy has the capacity to robustly encode material signatures, infer object composition and recover photometric parameters. This landmark text/reference presents a detailed analysis of spectral imaging, describing how it can be used in elegant and efficient ways for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications from surveillance and computational photography, to biosecurity and resource exploration. Topics and features: Discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation Examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery Describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra Reviews the use of imaging spectroscopy for material identification Explores the recovery of reflection geometry from image reflectance Investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view An essential resource for researchers and graduate students of computer vision and pattern recognition, this comprehensive introduction to imaging spectroscopy for scene analysis will also be of great use to practitioners interested in shape analysis employing polarimetric imaging, and material recognition and classification using hyperspectral or multispectral data.

Contents:

Introduction

Spectral Image Acquisition

Spectral Image Formation Process

Reflectance Modelling

Illuminant Power Spectrum

Photometric Invariance

Spectrum Representation

Material Discovery

Reflection Geometry

Polarisation of Light

Shape and Refractive Index from Polarisation.

Other Format:

Printed edition:

ISBN:

978-1-4471-4652-0

9781447146520

Access Restriction:

Restricted for use by site license.