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, lots of spaceborne and airborne sensors were hired to collect information about the earth's floor and atmosphere. As sensor know-how keeps to enhance, distant sensing facts with greater temporal, spectral, and spatial solution is changing into extra on hand. This frequent availability of large quantities of knowledge has necessitated the advance of effective facts processing suggestions for a wide selection of purposes. particularly, nice strides were made within the improvement of electronic snapshot processing thoughts for distant sensing info. The target has been effective dealing with of colossal quantities of information, fusion of knowledge from assorted sensors, class for picture interpretation, and improvement of undemanding items that permit wealthy visualization. This e-book offers a few new algorithms which have been constructed for top­ dimensional datasets, comparable to multispectral and hyperspectral imagery. The contents of the ebook are dependent totally on study conducted via a few individuals 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

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Typical spectral reflectance profile of vegetation that is scattered within the leaf is reflected back through the leaf surface, with a proportion transmitted through the leaf (Kumar 1998). SWIR reflectance is determined largely by moisture content (Kaufman and Remer 1994), with water absorption features centred primarily at 2660 nm and 2730 nm (Kumar et al. 2001). SWIR reflectance is also influenced by leaf biochemicals such as lignin, cellulose, starch, proteins and nitrogen (Guyot et al. 1989; Kumar et al.

Remote Sensing of Environment 70(2): 224-237 Buckingham B, Staenz K, Hollinger A (2002) Review of Canadian airborne and space activities in hyperspectral remote sensing. 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.

Hyperspectral Sensors and Applications 19 A significant advancement in hyperspectral remote sensing occurred when the Airborne VisiblelInfrared Imaging Spectrometer (AVIRIS) was proposed to NASA in 1983 (Vane et al. 1993). This sensor was the first to acquire image data in continuous narrow bands simultaneously in the visible to SWIR wavelength regions. Following approval in 1984, the first engineering flights occurred in early 1987 with data provided to scientific investigators shortly after. The AVIRIS was modified subsequently and flown throughout North America and Eurasia in the following 4 years and, since this period, this sensor has continued to be improved and is still providing some of the highest quality data to the scientific community today.

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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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