Collocation is a powerful technique in filtering the correlated part of a signal from noise. It is now widely applied in many research field (e.g. in geodesy to estimate the geoid or in photogrammetry to reconstruct a DEM). In this paper a 3-D collocation filter is developed from the theoretical and numerical point of view. The main theoretical problem, i.e. to find a suitable catalogue of positive definite functions, is solved and a proper set of positive definite functions for a 3-D process is defined; furthermore a package of FORTRAN 77 programs is developed to implement the method. To test this stochastic filter, a simulated 3-D signal was computed; the numerical procedure has proved to be effective.
3-D collocation filtering / R. Barzaghi, B. Crippa (PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING). - In: Close-Range Photogrammetry Meets Machine VisionBellingham, WA, United States : Publ by Int Soc for Optical Engineering, 1990. - pp. 886-893 (( convegno Close-Range Photogrammetry Meets Machine Vision tenutosi a Zurich nel 1990.
3-D collocation filtering
B. Crippa
1990
Abstract
Collocation is a powerful technique in filtering the correlated part of a signal from noise. It is now widely applied in many research field (e.g. in geodesy to estimate the geoid or in photogrammetry to reconstruct a DEM). In this paper a 3-D collocation filter is developed from the theoretical and numerical point of view. The main theoretical problem, i.e. to find a suitable catalogue of positive definite functions, is solved and a proper set of positive definite functions for a 3-D process is defined; furthermore a package of FORTRAN 77 programs is developed to implement the method. To test this stochastic filter, a simulated 3-D signal was computed; the numerical procedure has proved to be effective.
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