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Autocorrelation and regularization in digital images. II. Simple image models

IEEE Transactions on Geoscience and Remote SensingPublished 1 May 1989
David L.B. Jupp, Alan H. Strahler, Curtis E. Woodcock
Citations156
SJR quartileQ1
SJR score2.40
SNIP2.37

TL;DR

Using the results derived in Part I, the basic second-order, or covariance, properties of scenes modeled by simple disks of varying size and spacing after imaging into disk-shaped pixels are analyzed to explore the relationship between the image variograms and discrete object scene structure.

Abstract

For pt.I see ibid., vol.26, no.4, p.463-73, July 1988. The variogram function used in geostatistical analysis is a useful statistic in the analysis of remotely sensed images. Using the results derived in Part I, the basic second-order, or covariance, properties of scenes modeled by simple disks of varying size and spacing after imaging into disk-shaped pixels are analyzed to explore the relationship between the image variograms and discrete object scene structure. The models provide insight into the nature of real images of the Earth's surface and the tools for a complete analysis of the more complex case of three-dimensional illuminated discrete-object images.>

Keywords

Environmental Science