Ebook: Imaging Spectroscopy for Scene Analysis

This book presents a detailed analysis of spectral imaging, describing how it can be used 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. 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.

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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.

---

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.

Content:
Front Matter....Pages I-XVIII
Introduction....Pages 1-7
Spectral Image Acquisition....Pages 9-15
Spectral Image Formation Process....Pages 17-35
Reflectance Modelling....Pages 37-51
Illuminant Power Spectrum....Pages 53-61
Photometric Invariance....Pages 63-87
Spectrum Representation....Pages 89-140
Material Discovery....Pages 141-174
Reflection Geometry....Pages 175-207
Polarisation of Light....Pages 209-239
Shape and Refractive Index from Polarisation....Pages 241-263
Back Matter....Pages 265-269

---

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.

Content:
Front Matter....Pages I-XVIII
Introduction....Pages 1-7
Spectral Image Acquisition....Pages 9-15
Spectral Image Formation Process....Pages 17-35
Reflectance Modelling....Pages 37-51
Illuminant Power Spectrum....Pages 53-61
Photometric Invariance....Pages 63-87
Spectrum Representation....Pages 89-140
Material Discovery....Pages 141-174
Reflection Geometry....Pages 175-207
Polarisation of Light....Pages 209-239
Shape and Refractive Index from Polarisation....Pages 241-263
Back Matter....Pages 265-269
....