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Directional interpolation of multicomponent data
Author(s) -
Andersson Fredrik,
Ramírez Adriana Citlali,
Wiik Torgeir,
Nikitin Viktor V.
Publication year - 2017
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12478
Subject(s) - interpolation (computer graphics) , noise (video) , computer graphics , computer science , algorithm , field (mathematics) , derivative (finance) , bilinear interpolation , directional derivative , computational science , geology , computer graphics (images) , mathematics , mathematical analysis , artificial intelligence , computer vision , animation , financial economics , pure mathematics , economics , image (mathematics)
A method for interpolation of multicomponent streamer data based on using the local directionality structure is presented. The derivative components are used to estimate a vector field that locally describes the direction with the least variability. Given this vector field, the interpolation can be phrased in terms of the solution of a partial differential equation that describes how energy is transported between regions of missing data. The approach can be efficiently implemented using readily available routines for computer graphics. The method is robust to noise in the measurements and particularly towards high levels of low‐frequent noise that is present in the derivative components of the multicomponent streamer data.