Compressive sensing for seismic data reconstruction via fast projection onto convex sets based on seislet transform

• Published in: Journal of applied geophysics Vol. 130; pp. 194 - 208
• Main Authors: Gan, Shuwei, Wang, Shoudong, Chen, Yangkang, Chen, Xiaohong, Huang, Weiling, Chen, Hanming
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2016
• Subjects: Algorithms; Compressive sensing; Computational geometry; Convexity; Detection; Fast projection onto convex sets; Irregularly sampled seismic data; Projection; Reconstruction; Seislet transform; Seismic studies; Sparsity comparison; Transforms; Irregularly sampled seismic data; Seislet transform; Compressive sensing; Sparsity comparison; Fast projection onto convex sets

According to the compressive sensing (CS) theory in the signal-processing field, we proposed a new CS approach based on a fast projection onto convex sets (POCS) algorithm with sparsity constraint in the seislet transform domain. The seislet transform appears to be the sparest among the state-of-the...