Ultrasound Localisation Microscopy (ULM) is an imaging framework which consists of following ultrasound contrast agents, microbubbles, in time, on ultrasound images. The three main steps of ULM are: detecting microbubbles by reducing tissue signal, localizing them with subwavelength precision and tracking their trajectories. ULM performances were evaluated in different studies throughout metrics such as localisation accuracy or capacity to filter the tissues. In parallel, adaptive beamforming offers narrower Point Spread Function (PSF) and/or better tissue filtering than delay-and-sum method classically used within ULM. In this paper, the ability of adaptive beamformers to enhance ULM performances is evaluated, with a particular focus on the trade-off between acquisition time and bubble concentration to achieve super-resolution results.
Wind information on SAR images are essential to characterize a marine environment in offshore or coastal area. More and more applications require high resolution wind field estimation. In this article, classical wind wave direction estimation methods are reviewed as the spectral or gradient approaches. In addition, a way to enhance the spectral method with the Radon transform is proposed. The aim of this document is to determine which method provides greatest results when the resolution grid is finer. Therefore, the methods accuracy, fidelity and uncertainty are compared through a simulation study, a section with RadarSAT2 data in coastal area and another one with Sentinel-1 measurements in offshore area.
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