The design of two-dimensional gradient estimators based on one-dimensional operators

The design of two-dimensional gradient estimators based on one-dimensional operators

Two-dimensional (2-D) gradient estimators are some of the most useful tools in image processing. A computational procedure for the extension of one-dimensional (1-D) gradient estimators to two dimensions (2-D) is presented. The procedure is equivalent to the surface fitting method. It is, however, s...

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Veröffentlicht in:IEEE transactions on image processing 1996-01, Vol.5 (1), p.155-159
Hauptverfasser: Azaria, M., Vitsnudel, I., Zeevi, Y.Y.
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Exact sciences and technology
Filters
Image processing
Information, signal and communications theory
Interpolation
Kernel
Least squares approximation
Neural networks
Signal processing
Stress
Surface fitting
Symmetric matrices
Telecommunications and information theory
Two dimensional displays
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Zusammenfassung:Two-dimensional (2-D) gradient estimators are some of the most useful tools in image processing. A computational procedure for the extension of one-dimensional (1-D) gradient estimators to two dimensions (2-D) is presented. The procedure is equivalent to the surface fitting method. It is, however, simpler in design, as the design is 1-D rather than 2-D. Higher order derivative estimators can also be constructed by the same procedure.
ISSN:1057-7149
1941-0042
DOI:10.1109/83.481681