Green's Theorem for Sign Data
Author(s) -
Louis M. Houston
Publication year - 2012
Publication title -
isrn applied mathematics
Language(s) - English
Resource type - Journals
eISSN - 2090-5572
pISSN - 2090-5564
DOI - 10.5402/2012/539359
Subject(s) - sign (mathematics) , green's theorem , noise (video) , signal (programming language) , sign function , constant (computer programming) , mathematics , computer science , mathematical analysis , artificial intelligence , brouwer fixed point theorem , fixed point theorem , fundamental theorem of calculus , image (mathematics) , programming language
Sign data are the signs of signal added to noise. It is well known that a constant signal can be recovered from sign data. In this paper, we show that an integral over variant signal can be recovered from an integral over sign data based on the variant signal. We refer to this as a generalized sign data average. We use this result to derive a Green's theorem for sign data. Green's theorem is important to various seismic processing methods, including seismic migration. Results in this paper generalize reported results for 2.5D data volumes in which Green's theorem applies to sign data based only on traditional sign data recovery.
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