Related papers: A Statistical View on Synthetic Aperture Imaging f…
We propose a guidance strategy to optimize real-time synthetic aperture sampling for occlusion removal with drones by pre-scanned point-cloud data. Depth information can be used to compute visibility of points on the ground for individual…
Deep learning approaches require enough training samples to perform well, but it is a challenge to collect enough real training data and label them manually. In this letter, we propose the use of realistic synthetic data with a wide…
Synthetic Aperture Radar (SAR) images contain a huge amount of information, however, the number of practical use-cases is limited due to the presence of speckle noise in them. In recent years, deep learning based techniques have brought…
The goal of synthetic aperture imaging is to estimate the reflectivity of a remote region of interest by processing data gathered with a moving sensor which emits periodically a signal and records the backscattered wave. We introduce and…
Coded apertures, traditionally employed in x-ray astronomy for imaging celestial objects, are now being adapted for micro-scale applications, particularly in studying microscopic specimens with synchrotron light diffraction. In this paper,…
We consider synthetic aperture radar imaging of a region containing point-like targets. Measurements are the set of frequency responses to scattering by the targets taken over a collection of individual spatial locations along the flight…
Classical and more recently deep computer vision methods are optimized for visible spectrum images, commonly encoded in grayscale or RGB colorspaces acquired from smartphones or cameras. A more uncommon source of images exploited in the…
Synthetic Aperture Radar (SAR) offers all-weather, high-resolution imaging capabilities, but its complex imaging mechanism often poses challenges for interpretation. In response to these limitations, this paper introduces an innovative…
We have developed a new on-axis digital holographic technique, heterodyne holography. The resolution of this technique is limited mainly by the amount of data recorded on two-dimensional photodetectors, i.e., the number of pixels and their…
This thesis is concerned with problems related to Synthetic Aperture Radar (SAR). The thesis is structured as follows: The first chapter explains what SAR is, and the physical and mathematical background is illuminated. The following…
Synthetic Aperture Radar (SAR) images are a valuable asset for a wide variety of tasks. In the last few years, many websites have been offering them for free in the form of easy to manage products, favoring their widespread diffusion and…
Synthetic aperture radar (SAR) images are affected by a spatially-correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation. Despeckling is an important task that aims at removing such…
Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present…
Digital two-dimensional (2D) spatial sampling devices (such as charge-coupled device) have been widely used in various imaging systems, especially in computational imaging systems. However, the undersampling of digital sampling devices is a…
This book chapter describes how spectral correlations in scattered light fields can be utilized for high-precision time-of-flight sensing. The chapter should serve as a gentle introduction and is intended for computational imaging…
In this article, we evaluate unsupervised anomaly detection methods in multispectral images obtained with a wavelength-independent synthetic aperture sensing technique, called Airborne Optical Sectioning (AOS). With a focus on search and…
Synthetic aperture radar (SAR) is a tomographic sensor that measures 2D slices of the 3D spatial Fourier transform of the scene. In many operational scenarios, the measured set of 2D slices does not fill the 3D space in the Fourier domain,…
We use convolutional neural networks to recover images optically down-sampled by $6.7\times$ using coherent aperture synthesis over a 16 camera array. Where conventional ptychography relies on scanning and oversampling, here we apply…
Synthetic aperture sonar (SAS) measures a scene from multiple views in order to increase the resolution of reconstructed imagery. Image reconstruction methods for SAS coherently combine measurements to focus acoustic energy onto the scene.…
Recent advances in deep learning-based object detection techniques have revolutionized their applicability in several fields. However, since these methods rely on unwieldy and large amounts of data, a common practice is to download models…