This excellent reference focuses on advances in signal processing and exploitation techniques for optical remote sensing with a collection of state-of-the art algorithms for hyperspectral and multispectral imaging technologies. It is intended for advanced users, particularly graduate students and image scientists specializing in the field of optical remote sensing.
The authors have specifically addressed statistical pattern classification algorithms as well as target recognition algorithms for hyperspectral imaging. Readers will benefit from a review on kernel methods in remote sensing and decision fusion techniques for vegetation mapping.
Some readers might also be interested in multi-sensor fusion techniques, which are discussed in the context of fusing optical and SAR data for the vulnerability mapping of buildings. This cutting-edge publication includes a collection of images and graphics, processing technologies and parallel implementations with up-to-date references at the end of each chapter.
Review by Axel Mainzer Koenig, CEO, 21st Century Data Analysis, a division of Koenig & Associates, Inc., Portland, Ore., U.S.A.
The opinions expressed in the book review section are those of the reviewer and do not necessarily reflect those of OPN or OSA.