Performance comparison of total variation minimization and group sparse reconstructions for extended target imaging in multilayered dielectric media

Fauzia Ahmad; Wenji Zhang; Ahmad Hoorfar

doi:10.1117/12.2306692

14 May 2018 Performance comparison of total variation minimization and group sparse reconstructions for extended target imaging in multilayered dielectric media

Fauzia Ahmad, Wenji Zhang, Ahmad Hoorfar

Author Affiliations +

Proceedings Volume 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics; 106580I (2018) https://doi.org/10.1117/12.2306692
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Imaging of targets embedded in multilayered dielectric media has attracted growing interest in microwave remote sensing, nondestructive testing, ground penetrating radar, and urban sensing. Compressive sensing has been successfully applied in the aforementioned applications for efficient target imaging, leading to prompt actionable intelligence. Recently, a total variation minimization (TVM) based approach was proposed, which offers superior performance over standard L1- minimization based sparse reconstruction in terms of target shape reconstruction and distinguishing closely-spaced point targets from an extended target. Alternatively, group sparse reconstruction (GSR) schemes can also be employed to account for target extent. In this paper, we provide a performance comparison between TVM and GSR schemes for extended target imaging in multi-layered media using numerical electromagnetic data.

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Fauzia Ahmad, Wenji Zhang, and Ahmad Hoorfar "Performance comparison of total variation minimization and group sparse reconstructions for extended target imaging in multilayered dielectric media", Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 106580I (14 May 2018); https://doi.org/10.1117/12.2306692

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