Over the last fifty years, a large number of spaceborne and airborne sensors have been employed to gather information regarding the earth's surface and environment. As sensor technology continues to advance, remote sensing data with improved temporal, spectral, and spatial resolution is becoming more readily available. This widespread availability of enormous amounts of data has necessitated the development of efficient data processing techniques for a wide variety of applications. In particular, great strides have been made in the development of digital image processing techniques for remote sensing data. The goal has been efficient handling of vast amounts of data, fusion of data from diverse sensors, classification for image interpretation, and development of user-friendly products that allow rich visualization. This book presents some new algorithms that have been developed for high dimensional datasets, such as multispectral and hyperspectral imagery. The contents of the book are based primarily on research carried out by some members and alumni of the Sensor Fusion Laboratory at Syracuse University.Goetz AFH (ed) (1995) Imaging spectrometry for remote sensing: vision to reality in 15 years. ... 935-956 Green EP, Mumby PJ, Edwards AJ, Clark CD (1996) A review of remote sensing for the assessment and management of tropical coastal resources. ... In: Carmichael RC (ed), Practical handbook of physical properties of rocks and minerals, C.R.C. Press Inc., Boca Raton, Florida, pp 599-669 Irons J R, anbsp;...
|Title||:||Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data|
|Author||:||Pramod K. Varshney, Manoj K. Arora|
|Publisher||:||Springer Science & Business Media - 2004-08-12|