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Advances in Hyperspectral Image Processing Techniques (Hardcover)
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Advances in Hyperspectral Image Processing Techniques (Hardcover)
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Advances in Hyperspectral Image Processing Techniques Authoritative
and comprehensive resource covering recent hyperspectral imaging
techniques from theory to applications Advances in Hyperspectral
Image Processing Techniques is derived from recent developments of
hyperspectral imaging (HSI) techniques along with new applications
in the field, covering many new ideas that have been explored and
have led to various new directions in the past few years. The work
gathers an array of disparate research into one resource and
explores its numerous applications across a wide variety of
disciplinary areas. In particular, it includes an introductory
chapter on fundamentals of HSI and a chapter on extensive use of
HSI techniques in satellite on-orbit and on-board processing to aid
readers involved in these specific fields. The book's content is
based on the expertise of invited scholars and is categorized into
six parts. Part I provides general theory. Part II presents various
Band Selection techniques for Hyperspectral Images. Part III
reviews recent developments on Compressive Sensing for
Hyperspectral Imaging. Part IV includes Fusion of Hyperspectral
Images. Part V covers Hyperspectral Data Unmixing. Part VI offers
different views on Hyperspectral Image Classification. Specific
sample topics covered in Advances in Hyperspectral Image Processing
Techniques include: Two fundamental principles of hyperspectral
imaging Constrained band selection for hyperspectral imaging and
class information-based band selection for hyperspectral image
classification Restricted entropy and spectrum properties for
hyperspectral imaging and endmember finding in compressively sensed
band domain Hyperspectral and LIDAR data fusion, fusion of band
selection methods for hyperspectral imaging, and fusion using
multi-dimensional information Advances in spectral unmixing of
hyperspectral data and fully constrained least squares linear
spectral mixture analysis Sparse representation-based hyperspectral
image classification; collaborative hyperspectral image
classification; class-feature weighted hyperspectral image
classification; target detection approach to hyperspectral image
classification With many applications beyond traditional remote
sensing, ranging from defense and intelligence, to agriculture, to
forestry, to environmental monitoring, to food safety and
inspection, to medical imaging, Advances in Hyperspectral Image
Processing Techniques is an essential resource on the topic for
industry professionals, researchers, academics, and graduate
students working in the field.
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