Authoritative and comprehensive resource covering recent hyperspectral imaging techniques from theory to applications
Advanced Hyperspectral Image Processing Techniques is derived from recent development of hyperspectral imaging (HSI) techniques along with new applications in the field, covering many new ideas that have been explored and have led in various new directions in the past few years.
The work gathers an array of disparate research in a growing area into one resource and explores its numerous applications across a wide variety of industries. It also includes a section on the 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 describes hyperspectral data unmixing. Part II spans topics from hyperspectral target detection to hyperspectral image classification. Part III explains band selection for HSI. Part IV covers compressive sensing for HSI. Part V pertains to fusion for HSI. Part VI describes applications for HSI.
Specific sample topics covered in Advanced Hyperspectral Image Processing Techniques include:
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 of spectral-spatial methods for hyperspectral image classification Advances in spectral unmixing of hyperspectral data and fully constrained least squares linear spectral mixture analysis
With many applications beyond traditional remote sensing, ranging from defense and intelligence, to agriculture, to forestry, to environmental monitoring, to medical imaging, Advanced Hyperspectral Image Processing Techniques is an essential resource on the topic for industry professionals, researchers, academics, and graduate students working in the field.
