Loic Denis

Université Jean Monnet · Hubert Curien Laboratory

Synthetic aperture radar tomographic imaging reconstructs the three-dimensional reflectivity of a scene from a set of coherent acquisitions performed in an interferometric configuration. In forest areas, a large number of elements backscatter the radar signal within each resolution cell. To reconstruct the vertical reflectivity profile, state-of-th...

Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images. Tremendous progress has been achieved in the domain of single-image despeckling. Latest techniques rely on deep neural networks to restore the various structures and textures peculiar to SAR images. The availability of time series of SAR images o...

Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images. Tremendous progress has been achieved in the domain of single-image despeckling. Latest techniques rely on deep neural networks to restore the various structures and textures peculiar to SAR images. The availability of time series of SAR images o...

Reducing speckle and limiting the variations of the physical parameters in Synthetic Aperture Radar (SAR) images is often a key-step to fully exploit the potential of such data. Nowadays, deep learning approaches produce state of the art results in single-image SAR restoration. Nevertheless, huge multi-temporal stacks are now often available and co...

Synthetic aperture radar (SAR) images are widely used for Earth observation to complement optical imaging. By combining information on the polarization and the phase shift of the radar echos, SAR images offer high sensitivity to the geometry and materials that compose a scene. This information richness comes with a drawback inherent to all coherent...

We present a new method to achieve autofocus in digital holographic microscopy. The method is based on inserting calibrated objects into a sample placed on a slide. Reconstructing a hologram using the inverse problems approach makes it possible to precisely locate and measure the inserted objects and thereby derive the slide plane location. Numeric...

Remote sensing provides valuable information about objects and areas from a distance in either active (e.g., radar and lidar) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (active and passive) is often degraded by a variety of noise types and artifacts. Image restoration, w...

Speckle fluctuations seriously limit the interpretability of synthetic aperture radar (SAR) images. Speckle reduction has thus been the subject of numerous works spanning at least four decades. Techniques based on deep neural networks have recently achieved a new level of performance in terms of SAR image restoration quality. Beyond the design of s...

In-line digital holography is a simple yet powerful tool to image absorbing and/or phase objects. However, the holograms of interest are corrupted by the background signal due to unwanted scattering elements located in the optical path. Using only two holograms of the same object, shifted to different locations, an inverse problems approach is appl...

Speckle fluctuations seriously limit the interpretability of synthetic aperture radar (SAR) images. Speckle reduction has thus been the subject of numerous works spanning at least four decades. Techniques based on deep neural networks have recently achieved a new level of performance in terms of SAR image restoration quality. Beyond the design of s...

Angular and spectral differential imaging is an observational technique used in astronomy to study the close environment of stars. The relative angular motion and spectral scaling between on-axis and off-axis sources are exploited by processing techniques to separate two components: the residual light from the star and the light coming from surroun...

Remote sensing provides valuable information about objects or areas from a distance in either active (e.g., RADAR and LiDAR) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (both active and passive) is often degraded by a variety of noise types and artifacts. Image restoratio...

Monitoring of rivers is of major scientific and societal importance, due to the crucial resource they provide to human activities and the threats caused by flood events. Rapid revisit Synthetic Aperture Radar (SAR) sensors such as Sentinel-1 or the future Surface Water and Ocean Topography (SWOT) mission are indispensable tools to achieve all-weath...

Aims. The purpose of this paper is to describe a new post-processing algorithm dedicated to the reconstruction of the spatial distribution of light received from off-axis sources, in particular from circumstellar disks. Methods. Built on the recent PACO algorithm dedicated to the detection of point-like sources, the proposed method is based on the...

Speckle reduction is a key step in many remote sensing applications. By strongly affecting synthetic aperture radar (SAR) images, it makes them difficult to analyse. Due to the difficulty to model the spatial correlation of speckle, a deep learning algorithm with semi-supervision is proposed in this paper: SAR2SAR. Multi-temporal time series are le...

SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from stacks of SAR images. High-resolution satellites such as TerraSAR-X provide images that can be combined to produce 3-D models. In urban areas, sparsity priors are generally enforced during the tomographic inversion process in order to retrieve the location of scatterers seen wi...

The speckle phenomenon remains a major hurdle for the analysis of SAR images. The development of speckle reduction methods closely follows methodological progress in the field of image restoration. The advent of deep neural networks has offered new ways to tackle this longstanding problem. Deep learning for speckle reduction is a very active resear...

An adaptive optics system with a single deformable mirror is being implemented on the THEMIS 90cm solar telescope. This system is designed to operate in the visible and is required to be as robust as possible in order to deliver the best possible correction in any atmospheric conditions, even if wavefronts are sensed on some low-contrast solar gran...

This paper presents a despeckling method for Sentinel-1 GRD images based on the recently proposed framework "SAR2SAR": a self-supervised training strategy. Training the deep neural network on collections of Sentinel 1 GRD images leads to a despeckling algorithm that is robust to space-variant spatial correlations of speckle. Despeckled images impro...

Deep learning approaches show unprecedented results for speckle reduction in SAR amplitude images. The wide availability of multi-temporal stacks of SAR images can improve even further the quality of denoising. In this paper, we propose a flexible yet efficient way to integrate temporal information into a deep neural network for speckle suppression...

A new method to achieve autofocus in digital holography is proposed. It is based on the insertion of calibrated objects in the sample and the use of a robust algorithm to locate these objects.

We propose to reconstruct biological samples using calibration beads to perform numerical autofocusing in in-line holographic microscopy. The approach is based on a joint inversion using both a parametric and a regularized inversion method.

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) images. Many different schemes have been proposed for the restoration of intensity SAR images. Among the different possible approaches, methods based on convolutional neural networks (CNNs) have recently shown to reach state-of-the-art performance for SAR image restoration....

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) images. Many different schemes have been proposed for the restoration of intensity SAR images. Among the different possible approaches, methods based on convolutional neural networks (CNNs) have recently shown to reach state-of-the-art performance for SAR image restoration....

Speckle reduction is a key step in many remote sensing applications. By strongly affecting synthetic aperture radar (SAR) images, it makes them difficult to analyse. Due to the difficulty to model the spatial correlation of speckle, a deep learning algorithm with self-supervision is proposed in this paper: SAR2SAR. Multi-temporal time series are le...

Context. Exoplanet detection and characterization by direct imaging both rely on sophisticated instruments (adaptive optics and coronagraph) and adequate data processing methods. Angular and spectral differential imaging (ASDI) combines observations at different times and a range of wavelengths in order to separate the residual signal from the host...

Cross-track synthetic aperture radar (SAR) interferometry is a powerful technique that analyzes the phase shift each pixel undergoes between acquisitions of the same scene with just a slight change of viewpoint. These phase shifts provide information about the topography and, when more than two acquisitions are available at different dates, about p...

Context. The improvement of large size detectors permitted the development of integral field spectrographs (IFSs) in astronomy. Spectral information for each spatial element of a two-dimensional field of view is obtained thanks to integral field units that spread the spectra on the 2D grid of the sensor. Aims. Here we aim to solve the inherent issu...

Context. The detection of exoplanets by direct imaging is very challenging. It requires an extreme adaptive-optics (AO) system and a coronagraph as well as suitable observing strategies. In angular differential imaging, the signal-to-noise ratio is improved by combining several observations. Aims. Due to the evolution of the observation conditions...

In several areas of imaging, it is necessary to detect the weak signal of a known pattern superimposed over a background. Because of its temporal fluctuations, the background may be difficult to suppress. Detection of the pattern then requires a statistical modeling of the background. Due to difficulties related to (i) the estimation of the spatial...

One of the main objectives of the surface water and ocean topography (SWOT) mission, scheduled for launch in 2021, is to measure inland water levels using synthetic aperture radar (SAR) interferometry. A key step toward this objective is to precisely detect water areas. In this article, we present a method to detect water in SWOT images. Water is d...

This paper includes a tutorial on how to reconstruct in-line holograms using an inverse problems approach, starting with modeling the observations, selecting regularizations and constraints, and ending with the design of a reconstruction algorithm. A special focus is placed on the connections between the numerous alternating projections strategies...

SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from stacks of SAR images. High resolution satellites such as TerraSAR-X provide images that can be combined to produce 3-D models. In urban areas, sparsity priors are generally enforced during the tomographic inversion process in order to retrieve the location of scatterers seen wi...

In-line digital holography is a simple yet powerful tool to image absorbing and/or phase objects. Nevertheless, the loss of the phase of the complex wavefront on the sensor can be critical in the reconstruction process. The simplicity of the setup must thus be counterbalanced by dedicated reconstruction algorithms, such as inverse approaches, in or...

We propose to reconstruct in-line holograms using a joint forward model on samples composed of a simple subpart estimated by model fitting and a complex shape subpart reconstructed using numerical (pixel-based) regularized inversion.

Several reconstruction approaches based on inverse problems (also called compressive sensing, Bayesian approaches, model fitting) have been proposed recently in digital holography. We demonstrate how such approaches improve hologram reconstruction in various configurations and with diverse object types.

Context . The detection of exoplanets by direct imaging is an active research topic in astronomy. Even with the coupling of an extreme adaptive-optics system with a coronagraph, it remains challenging due to the very high contrast between the host star and the exoplanets. Aims. The purpose of this paper is to describe a method, named PACO, dedicate...

Reconstruction of phase objects is a central problem in digital holography, whose various applications include microscopy, biomedical imaging, and fluid mechanics. Starting from a single in-line hologram, there is no direct way to recover the phase of the diffracted wave in the hologram plane. The reconstruction of absorbing and phase objects there...

Synthetic aperture radar (SAR) images display very high dynamic ranges. Man-made structures (like buildings or power towers) produce echoes that are several orders of magnitude stronger than echoes from diffusing areas (vegetated areas) or from smooth surfaces (e.g., roads). The impulse response of the SAR imaging system is, thus, clearly visible a...

This chapter is dedicated to very-high-resolution (VHR) SAR imagery, including interferometric applications. First, the principles of SAR data acquisition are presented as well as the different types of configurations. The widely adopted Gaussian complex model of fully developed speckle is described as well as more advanced statistical models for V...

In this paper, we propose a fast and efficient multitemporal despeckling method. The key idea of the proposed approach is the use of the ratio image, provided by the ratio between an image and the temporal mean of the stack. This ratio image is easier to denoise than a single image thanks to its improved stationarity. Besides, temporally stable thi...