Read e-book online Advanced Image Processing Techniques for Remotely Sensed PDF

By Professor Dr. Pramod K. Varshney, Dr. Manoj K. Arora (auth.)

ISBN-10: 3642060013

ISBN-13: 9783642060014

ISBN-10: 3662056054

ISBN-13: 9783662056059

Over the final fifty years, various spaceborne and airborne sensors were hired to assemble information about the earth's floor and setting. As sensor know-how keeps to strengthen, distant sensing info with enhanced temporal, spectral, and spatial answer is turning into extra available. This frequent availability of large quantities of information has necessitated the advance of effective info processing strategies for a wide selection of functions. particularly, nice strides were made within the improvement of electronic snapshot processing recommendations for distant sensing information. The objective has been effective dealing with of enormous quantities of information, fusion of information from different sensors, type for photograph interpretation, and improvement of easy items that let wealthy visualization. This e-book offers a few new algorithms which were built for primeĀ­ dimensional datasets, resembling multispectral and hyperspectral imagery. The contents of the publication are established totally on learn performed by means of a few individuals and alumni of the Sensor Fusion Laboratory at Syracuse University.

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Extra resources for Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

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S Software for Hyperspectral Processing The datasets originating from hyperspectral sensors are complex and cannot be adequately analyzed using the more traditional image processing packages. 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.

Canadian Aeronautics and Space Journal 48(1): 115-121 Carranza EJM, Hale M (2002) Mineral imaging with Landsat Thematic Mapper data for hydrothermal alteration mapping in heavily vegetated terrain. International Journal of Remote Sensing 23(22): 4827-4852 Cervelle B. (1991) Application of mineralogical constraints to remote-sensing. European Journal of Mineralogy 3(4): 677-688 42 1: Richard lucas, Aled Rowlands, Olaf Niemann, Ray Merton Chabrillat S, Goetz AFH, Krosley L, Olsen HW (2002) Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution.

3 Temporal Resolution The temporal resolution refers to the frequency of observation by sensors. Until the advent of hyperspectral data from spaceborne sensors, observations were obtained on an 'as needs' basis. Due primarily to limitations of cost, few multitemporal datasets have been produced. As a result, the complex timeseries of hyperspectral dataset acquisitions targeting geology, soil, and plant applications constructed primarily of AVIRIS, HyMap, and CHRIS data (1992current) over Jasper Ridge in California (Merton 1999) perhaps represents one of the few comprehensive datasets available.

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Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by Professor Dr. Pramod K. Varshney, Dr. Manoj K. Arora (auth.)

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