Springer Imaging Spectroscopy for Scene Analysis (Advances in Computer Vision and Pattern Recognition)

Product Description This book presents a detailed analysis of spectral imaging, describing how it can be used in material identification, object recognition and scene understanding. It reviews a range of applications, from computational photography to biosecurity. Review “This book is a significant and timely contribution in the area of computer vision for imaging spectroscopy for scene analysis. … This book would be useful to various practitioners and scientists who are working in the area of color image processing, optics, graphics, object reconstruction etc. … The book can be useful for researchers and academics who want to understand imaging spectroscopy for scene understanding. It is a valuable contribution in the area of hyperspectral imaging … .” (Dr. Tanish Zaveri and Bhupendra Fataniya, IAPR Newsletter, Vol. 37 (4), 2015) From the Back Cover 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. About the Author Dr. Antonio Robles-Kelly is a Principal Researcher at NICTA, where he leads the Spectral Imaging project. He is also an Adjunct Associate Professor at the Australian National University and Conjoint Senior Lecturer at the University of New South Wales, Australia. Dr. Cong Phuoc Huynh is a Researcher at NICTA, and an Adjunct Research Fellow at the Australian National University, Australia.