By Professor Dr. Pramod K. Varshney, Dr. Manoj K. Arora (auth.)
Over the final fifty years, plenty of spaceborne and airborne sensors were hired to assemble information about the earth's floor and atmosphere. As sensor know-how keeps to increase, distant sensing info with stronger temporal, spectral, and spatial solution is turning into extra available. This frequent availability of large quantities of information has necessitated the advance of effective information processing ideas for a large choice of functions. particularly, nice strides were made within the improvement of electronic snapshot processing recommendations for distant sensing facts. The objective has been effective dealing with of mammoth quantities of knowledge, fusion of information from assorted sensors, type for photo interpretation, and improvement of uncomplicated items that let wealthy visualization. This publication offers a few new algorithms which were constructed for prime dimensional datasets, comparable to multispectral and hyperspectral imagery. The contents of the ebook are established totally on study performed via a few participants and alumni of the Sensor Fusion Laboratory at Syracuse University.
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Additional resources for Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data
Parallel to NASA's development of the AVIRIS sensor have been a number of commercial ventures where hyperspectral sensors have been designed and deployed. Since 1978, the Canadian company ITRES has paved the way for airborne hyperspectral remote sensing through the development of the Compact Airborne Spectrographic Imager (CASI), which was based on the earlier FLI (Hollinger et al. 1987). This sensor has been in operation since 1989 and was used not only for commercial operations in the private sector but also for research projects.
LANDSAT-7 ETM+). Even so, this sensor remains more an experimental research tool rather than one that is ready for general applications development, due largely to the limited swath width and the generally poorly understood radiometry. The CHRIS sensor, although not observing in SWIR regions, has given a greater opportunity to explore the bidirectional capabilities and information content of hyperspectral data with applications in land surface biochemical and biophysical property retrieval and water characterisation.
Significant research has therefore been carried out to develop algorithms that can be incorporated into commercially available software. At the time of writing two of the more commonly used packages for hyperspectral image processing have been produced by Research Systems Inc. A. and PCI Geomatics, Canada. 5. It should be noted that many of the algorithms used for hyperspectral imaging applications presented in this book are of an advanced nature and are still under research and development. 5.
Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by Professor Dr. Pramod K. Varshney, Dr. Manoj K. Arora (auth.)