Sparsity Regularized Nonlinear Inversion for Microwave Imaging
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2757087
Abstract: We present a novel microwave imaging technique for sparse domain imaging applications. In the proposed method, inverse scattering algorithm modified gradient method (MGM) is combined with a fast iterative shrinkage-thresholding algorithm to improve the resolution… read more here.
Keywords: microwave imaging; proposed method; sparsity regularized; domain ... See more keywords
A Hybrid Iterative Thresholding Method for Solving Sparsity-Regularized Linear Inverse Problems and Its Application in Seismic Sparse-Spike Deconvolution
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3278026
Abstract: Sparsity-regularized linear inverse problem has served as the base in many disciplines, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, and so forth. The iterative hard thresholding algorithm… read more here.
Keywords: linear inverse; sparsity regularized; regularized linear; method ... See more keywords
An Iterative Re-Weighting Algorithm for Element to Solve Sparsity-Regularized Linear Inverse Problem and an Application in Sparse-Spike Deconvolution of Seismic Data
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2025.3574446
Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, etc. This method offers greater flexibility in solving… read more here.
Keywords: sparse regularization; regularized linear; sparsity regularized; linear inverse ... See more keywords