Hybrid Low-Rank and Sparsity Constraint With Hankel Structure Preservation for Simultaneous Seismic Reconstruction and Denoising
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3262603
Abstract: As acquired seismic data is usually incomplete and noisy, simultaneous reconstruction and denoising is an extremely important step for the accurate interpretation of seismic data and subsequent processing. We propose a hybrid low-rank and sparsity… read more here.
Keywords: sparsity; reconstruction; reconstruction denoising; hankel structure ... See more keywords
Seismic Data Reconstruction and Denoising by Enhanced Hankel Low-Rank Matrix Estimation
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3267941
Abstract: Seismic data reconstruction and denoising play a fundamental role in most seismic data processing algorithms which are often designed for regularly sampled and reliable data. Using the fact that the (block) Hankel matrix formulated from… read more here.
Keywords: low rank; reconstruction; reconstruction denoising; data reconstruction ... See more keywords
Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data
Sign Up to like & getrecommendations! Published in 2017 at "Geophysics"
DOI: 10.1190/geo2016-0557.1
Abstract: ABSTRACTWe have determined an approach for simultaneous reconstruction and denoising of 3D seismic data with randomly missing traces. The core in simultaneous reconstruction and denoising of 3D seismic data is the choice of constraint method.… read more here.
Keywords: simultaneous reconstruction; seismic data; constraint; reconstruction denoising ... See more keywords