Multithreading Based Parallel Processing for Image Geometric Coregistration in SAR Interferometry

Imperatore, Pasquale; Sansosti, E.

doi:10.3390/rs13101963

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…In future work, we also plan to realize an efficient implementation of the adopted processing strategy for SAR image calibration, which is indeed amenable to be inherently parallelized by employing shared-memory architectures and multithreading [36] or advances in GPU technology [37]. The relevant parallel prototype will boost its operational use in large-scale SAR data processing.…”

Section: Discussionmentioning

confidence: 99%

SAR Radiometric Calibration Based on Differential Geometry: From Theory to Experimentation on SAOCOM Imagery

Imperatore

Martino

2023

Remote Sensing

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The modeling and simulation of topography-induced imaging distortions are crucial for consistent radiometric information exploitation in current and forthcoming SAR-based Earth observation missions with a high spatial and temporal resolution, with relevance in several applications. In this paper, for the first time, we specifically investigate the compensation of topography-induced radiometric distortions affecting SAR images acquired by the L-band Argentinian satellite SAOCOM. We adopt a recently developed calibration method relying on an analytical formulation derived in the rigorous framework of the differential geometry of surfaces. We first provide an original interpretation of the analytical formulation, thus providing further insights into the relevant area-stretching-based formalism. Then, the numerical implementation of the method is specialized to systematically process the data acquired by SAOCOM sensors; hence, the resulting sensor-specific prototype solution processor is employed in this study. Finally, experiments performed over a real scenario in the southern part of Italy, characterized by large topography variations, are presented and discussed, thus elucidating the effectiveness of the adopted method applied to SAOCOM images. The adopted effective SAR calibration strategy opens up the way to its operational use in large-scale SAOCOM data processing.

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Section: Discussionmentioning

confidence: 99%

SAR Radiometric Calibration Based on Differential Geometry: From Theory to Experimentation on SAOCOM Imagery

Imperatore

Martino

2023

Remote Sensing

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“…SAR image coregistration is a fundamental preliminary operation for geometrically aligning two or more complex images of the same scene (acquired from different viewpoints, times, or sensors), thus ensuring that homologous pixels in all the images correspond to the same target on the ground. Since it needs to be performed with subpixel accuracy to preserve phase information, thus enabling IC evaluation, SAR image coregistration might be a computationally demanding task; however, efficient implementations are available [46].…”

Section: General Pre-processing Operationsmentioning

confidence: 99%

Flood Detection with SAR: A Review of Techniques and Datasets

Amitrano,

Di Martino,

Di Simone

et al. 2024

Remote Sensing

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Floods are among the most severe and impacting natural disasters. Their occurrence rate and intensity have been significantly increasing worldwide in the last years due to climate change and urbanization, bringing unprecedented effects on human lives and activities. Hence, providing a prompt response to flooding events is of crucial relevance for humanitarian, social and economic reasons. Satellite remote sensing using synthetic aperture radar (SAR) offers a great deal of support in facing flood events and mitigating their effects on a global scale. As opposed to multi-spectral sensors, SAR offers important advantages, as it enables Earth’s surface imaging regardless of weather and sunlight illumination conditions. In the last decade, the increasing availability of SAR data, even at no cost, thanks to the efforts of international and national space agencies, has been deeply stimulating research activities in every Earth observation field, including flood mapping and monitoring, where advanced processing paradigms, e.g., fuzzy logic, machine learning, data fusion, have been applied, demonstrating their superiority with respect to traditional classification strategies. However, a fair assessment of the performance and reliability of flood mapping techniques is of key importance for an efficient disasters response and, hence, should be addressed carefully and on a quantitative basis trough synthetic quality metrics and high-quality reference data. To this end, the recent development of open SAR datasets specifically covering flood events with related ground-truth reference data can support thorough and objective validation as well as reproducibility of results. Notwithstanding, SAR-based flood monitoring still suffers from severe limitations, especially in vegetated and urban areas, where complex scattering mechanisms can impair an accurate extraction of water regions. All such aspects, including classification methodologies, SAR datasets, validation strategies, challenges and future perspectives for SAR-based flood mapping are described and discussed.

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“…A master image is the one that is being compared. A coregistration is performed to the master and slave images [5] . Offset Tracking through the SAR data is most commonly used for the estimation of Glacier Velocity.…”

Section: 𝑖 = 𝐷𝑁 𝐴mentioning

confidence: 99%

Line-of-Sight Glacier Velocity Estimation of Transboundary Glaciers in the Eastern Himalayas Using High-Resolution TerraSAR-X Data

et al. 2023

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Glacier velocity is one of the critical parameters for understanding the current health status of a glacier. According to the momentum law, mass is inversely proportional to velocity. Higher velocity may indicate lesser mass. Fifteen transboundary glaciers from the eastern Himalayas in the vicinity of India, Nepal, Bhutan, and China are chosen for the estimation of glacier velocity. These glaciers are Changshang, Rathong, South Lhonak, South Simvo, Talung, Tongshiong, Yalung, Zemu, Glacier 2, Glacier 3, Kaer, Ktr Gr 193, Middle Lhonak, North Lhonak, and Ktr Gr 171 (Lhonak Nepal) covering total area of 440.92 km 2 . A remote sensing and GIS-based approach is considered for the study. High-resolution Synthetic Aperture Radar data of TerraSAR-X was acquired from the German Aerospace Center (DLR) by European Space Agency for study area in the year 2020-2021. Satellite data are preprocessed using radiometric calibration and multi-look for speckle noise reduction. These datasets are co-registered using SRTM Digital Elevation Model. Offset Tracking is applied to estimate the glacier velocity. The maximum velocity in all glaciers ranged from 14.31-84.26ma -1 . The average velocity ranged from 1.78-7.09ma −1 . The glacier having highest average velocity is South Lhonak glacier. This glacier is melting rapidly in the last few decades. Near the snout of this glacier lies a glacial lake made up of a moraine dam. For quality assessment, latest field-based results of 2018 and observed results of 2021 were compared. It has been noticed that there is a variation of approximately 10%.

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Multithreading Based Parallel Processing for Image Geometric Coregistration in SAR Interferometry

Cited by 6 publications

References 39 publications

SAR Radiometric Calibration Based on Differential Geometry: From Theory to Experimentation on SAOCOM Imagery

SAR Radiometric Calibration Based on Differential Geometry: From Theory to Experimentation on SAOCOM Imagery

Flood Detection with SAR: A Review of Techniques and Datasets

Line-of-Sight Glacier Velocity Estimation of Transboundary Glaciers in the Eastern Himalayas Using High-Resolution TerraSAR-X Data

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