Compressive sensing in electromagnetics-a review
Several problems arising in electromagnetics can be directly formulated or suitably recast for
an effective solution within the compressive sensing (CS) framework. This has motivated a …
an effective solution within the compressive sensing (CS) framework. This has motivated a …
Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends
Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
Sparse microwave imaging: Principles and applications
BC Zhang, W Hong, YR Wu - Science China Information Sciences, 2012 - Springer
This paper provides principles and applications of the sparse microwave imaging theory and
technology. Synthetic aperture radar (SAR) is an important method of modern remote …
technology. Synthetic aperture radar (SAR) is an important method of modern remote …
Multimodal remote sensing image segmentation with intuition-inspired hypergraph modeling
Multimodal remote sensing (RS) image segmentation aims to comprehensively utilize
multiple RS modalities to assign pixel-level semantics to the studied scenes, which can …
multiple RS modalities to assign pixel-level semantics to the studied scenes, which can …
A sparse image fusion algorithm with application to pan-sharpening
Data provided by most optical Earth observation satellites such as IKONOS, QuickBird, and
GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and …
GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and …
SEN12MS-CR-TS: A remote-sensing data set for multimodal multitemporal cloud removal
About half of all optical observations collected via spaceborne satellites are affected by haze
or clouds. Consequently, cloud coverage affects the remote-sensing practitioner's …
or clouds. Consequently, cloud coverage affects the remote-sensing practitioner's …
Sparsity-driven synthetic aperture radar imaging: Reconstruction, autofocusing, moving targets, and compressed sensing
This article presents a survey of recent research on sparsity-driven synthetic aperture radar
(SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal …
(SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal …
Very-high-resolution airborne synthetic aperture radar imaging: Signal processing and applications
During the last decade, synthetic aperture radar (SAR) became an indispensable source of
information in Earth observation. This has been possible mainly due to the current trend …
information in Earth observation. This has been possible mainly due to the current trend …
CAESAR: An approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing
Synthetic aperture radar (SAR) tomography has been strongly developed in the last years
for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors …
for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors …
Super-resolution power and robustness of compressive sensing for spectral estimation with application to spaceborne tomographic SAR
We address the problem of resolving two closely spaced complex-valued points from N
irregular Fourier do-main samples. Although this is a generic super-resolution (SR) problem …
irregular Fourier do-main samples. Although this is a generic super-resolution (SR) problem …