Matches in SemOpenAlex for { <https://semopenalex.org/work/W2346276847> ?p ?o ?g. }
- W2346276847 endingPage "33" @default.
- W2346276847 startingPage "21" @default.
- W2346276847 abstract "The hyperbolic Radon transform is a commonly used tool in seismic processing, for instance in seismic velocity analysis, data interpolation and for multiple removal. A direct implementation by summation of traces with different moveouts is computationally expensive for large data sets. In this paper we present a new method for fast computation of the hyperbolic Radon transforms. It is based on using a log-polar sampling with which the main computational parts reduce to computing convolutions. This allows for fast implementations by means of FFT. In addition to the FFT operations, interpolation procedures are required for switching between coordinates in the time-offset; Radon; and log-polar domains. Graphical Processor Units (GPUs) are suitable to use as a computational platform for this purpose, due to the hardware supported interpolation routines as well as optimized routines for FFT. Performance tests show large speed-ups of the proposed algorithm. Hence, it is suitable to use in iterative methods, and we provide examples for data interpolation and multiple removal using this approach." @default.
- W2346276847 created "2016-06-24" @default.
- W2346276847 creator A5015881443 @default.
- W2346276847 creator A5018464265 @default.
- W2346276847 creator A5071831042 @default.
- W2346276847 creator A5076684330 @default.
- W2346276847 date "2017-08-01" @default.
- W2346276847 modified "2023-10-14" @default.
- W2346276847 title "Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates" @default.
- W2346276847 cites W1902462946 @default.
- W2346276847 cites W1979887666 @default.
- W2346276847 cites W1988909113 @default.
- W2346276847 cites W1997096414 @default.
- W2346276847 cites W2003410902 @default.
- W2346276847 cites W2010122118 @default.
- W2346276847 cites W2026439899 @default.
- W2346276847 cites W2027069532 @default.
- W2346276847 cites W2030815520 @default.
- W2346276847 cites W2038019732 @default.
- W2346276847 cites W2052523317 @default.
- W2346276847 cites W2055689533 @default.
- W2346276847 cites W2056160384 @default.
- W2346276847 cites W2061258853 @default.
- W2346276847 cites W2099944953 @default.
- W2346276847 cites W2100849374 @default.
- W2346276847 cites W2105304793 @default.
- W2346276847 cites W2108769192 @default.
- W2346276847 cites W2110057212 @default.
- W2346276847 cites W2113825554 @default.
- W2346276847 cites W2115706991 @default.
- W2346276847 cites W2126068349 @default.
- W2346276847 cites W2135519048 @default.
- W2346276847 cites W2138950524 @default.
- W2346276847 cites W2144079431 @default.
- W2346276847 cites W2164620857 @default.
- W2346276847 cites W2221433403 @default.
- W2346276847 cites W275242509 @default.
- W2346276847 cites W3121745410 @default.
- W2346276847 cites W3154671241 @default.
- W2346276847 doi "https://doi.org/10.1016/j.cageo.2017.04.013" @default.
- W2346276847 hasPublicationYear "2017" @default.
- W2346276847 type Work @default.
- W2346276847 sameAs 2346276847 @default.
- W2346276847 citedByCount "20" @default.
- W2346276847 countsByYear W23462768472017 @default.
- W2346276847 countsByYear W23462768472018 @default.
- W2346276847 countsByYear W23462768472019 @default.
- W2346276847 countsByYear W23462768472020 @default.
- W2346276847 countsByYear W23462768472021 @default.
- W2346276847 countsByYear W23462768472022 @default.
- W2346276847 countsByYear W23462768472023 @default.
- W2346276847 crossrefType "journal-article" @default.
- W2346276847 hasAuthorship W2346276847A5015881443 @default.
- W2346276847 hasAuthorship W2346276847A5018464265 @default.
- W2346276847 hasAuthorship W2346276847A5071831042 @default.
- W2346276847 hasAuthorship W2346276847A5076684330 @default.
- W2346276847 hasBestOaLocation W23462768472 @default.
- W2346276847 hasConcept C11413529 @default.
- W2346276847 hasConcept C121332964 @default.
- W2346276847 hasConcept C121684516 @default.
- W2346276847 hasConcept C137800194 @default.
- W2346276847 hasConcept C159694833 @default.
- W2346276847 hasConcept C175291020 @default.
- W2346276847 hasConcept C197231052 @default.
- W2346276847 hasConcept C199360897 @default.
- W2346276847 hasConcept C31972630 @default.
- W2346276847 hasConcept C41008148 @default.
- W2346276847 hasConcept C45374587 @default.
- W2346276847 hasConcept C459310 @default.
- W2346276847 hasConcept C502989409 @default.
- W2346276847 hasConcept C545943180 @default.
- W2346276847 hasConcept C62520636 @default.
- W2346276847 hasConcept C75172450 @default.
- W2346276847 hasConceptScore W2346276847C11413529 @default.
- W2346276847 hasConceptScore W2346276847C121332964 @default.
- W2346276847 hasConceptScore W2346276847C121684516 @default.
- W2346276847 hasConceptScore W2346276847C137800194 @default.
- W2346276847 hasConceptScore W2346276847C159694833 @default.
- W2346276847 hasConceptScore W2346276847C175291020 @default.
- W2346276847 hasConceptScore W2346276847C197231052 @default.
- W2346276847 hasConceptScore W2346276847C199360897 @default.
- W2346276847 hasConceptScore W2346276847C31972630 @default.
- W2346276847 hasConceptScore W2346276847C41008148 @default.
- W2346276847 hasConceptScore W2346276847C45374587 @default.
- W2346276847 hasConceptScore W2346276847C459310 @default.
- W2346276847 hasConceptScore W2346276847C502989409 @default.
- W2346276847 hasConceptScore W2346276847C545943180 @default.
- W2346276847 hasConceptScore W2346276847C62520636 @default.
- W2346276847 hasConceptScore W2346276847C75172450 @default.
- W2346276847 hasFunder F4320321761 @default.
- W2346276847 hasFunder F4320322581 @default.
- W2346276847 hasLocation W23462768471 @default.
- W2346276847 hasLocation W23462768472 @default.
- W2346276847 hasLocation W23462768473 @default.
- W2346276847 hasOpenAccess W2346276847 @default.
- W2346276847 hasPrimaryLocation W23462768471 @default.
- W2346276847 hasRelatedWork W1502227748 @default.
- W2346276847 hasRelatedWork W2050711336 @default.