NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Autocorrelation and regularization in digital images. I - Basic theorySpatial structure occurs in remotely sensed images when the imaged scenes contain discrete objects that are identifiable in that their spectral properties are more homogeneous within than between them and other scene elements. The spatial structure introduced is manifest in statistical measures such as the autocovariance function and variogram associated with the scene, and it is possible to formulate these measures explicitly for scenes composed of simple objects of regular shapes. Digital images result from sensing scenes by an instrument with an associated point spread function (PSF). Since there is averaging over the PSF, the effect, termed regularization, induced in the image data by the instrument will influence the observable autocovariance and variogram functions of the image data. It is shown how the autocovariance or variogram of an image is a composition of the underlying scene covariance convolved with an overlap function, which is itself a convolution of the PSF. The functional form of this relationship provides an analytic basis for scene inference and eventual inversion of scene model parameters from image data.
Document ID
19880060213
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Jupp, David L. B.
(CSIRO Div. of Water Resources Research, Canberra, Australia)
Strahler, Alan H.
(New York, City University NY, United States)
Woodcock, Curtis E.
(Boston University MA, United States)
Date Acquired
August 13, 2013
Publication Date
July 1, 1988
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: 26
ISSN: 0196-2892
Subject Category
Instrumentation And Photography
Accession Number
88A47440
Funding Number(s)
CONTRACT_GRANT: NAGW-735
CONTRACT_GRANT: NAG5-276
CONTRACT_GRANT: NAG5-273
CONTRACT_GRANT: NAS9-16664
Distribution Limits
Public
Copyright
Other

Available Downloads

There are no available downloads for this record.
No Preview Available