2.2k citations · 2.7k across the 28 of their papers we have counts for
28 papers
Deep Learning for Atmospheric Turbulence Mitigation: A Comparison Between GANs and Transformers
Juan S. Carrillo, Jérôme Gilles
Atmospheric turbulence creates complex spatial and temporal distortions that significantly reduce image quality. This work compares two deep learning methods for turbulence reducti…
Fast probabilistic snake algorithm
Jérôme Gilles, Bertrand Collin
Few people use the probability theory in order to achieve image segmentation with snake models. In this article, we are presenting an active contour algorithm based on a probabilit…
Noisy image decomposition: a new structure, texture and noise model based on local adaptivity
Jerome Gilles
These last few years, image decomposition algorithms have been proposed to split an image into two parts: the structures and the textures. These algorithms are not adapted to the c…
Restoration algorithms and system performance evaluation for active imagers
Jerome Gilles
This paper deals with two fields related to active imaging system. First, we begin to explore image processing algorithms to restore the artefacts like speckle, scintillation and i…
Atmospheric turbulence restoration by diffeomorphic image registration and blind deconvolution
Jerome Gilles, Tristan Dagobert, Carlo De Franchis
A novel approach is presented in this paper to improve images which are altered by atmospheric turbulence. Two new algorithms are presented based on two combinations of a blind dec…
METRIC: a complete methodology for performances evaluation of automatic target Detection, Recognition and Tracking algorithms in infrared imagery
Jérôme Gilles, Stéphane Landeau, Tristan Dagobert +4
In this communication, we deal with the question of automatic target detection, recognition and tracking (ATD/R/T) algorithms performance assessment. We propose a complete methodol…
Image Decomposition: Theory, Numerical Schemes, and Performance Evaluation
Jerome Gilles
This paper describes the many image decomposition models that allow to separate structures and textures or structures, textures, and noise. These models combined a total variation…
Properties of BV-G structures + textures decomposition models. Application to road detection in satellite images
Jerome Gilles, Yves Meyer
In this paper we present some theoretical results about a structures-textures image decomposition model which was proposed by the second author. We prove a theorem which gives the…
Fried deconvolution
Jerome Gilles, Stanley Osher
In this paper we present a new approach to deblur the effect of atmospheric turbulence in the case of long range imaging. Our method is based on an analytical formulation, the Frie…
Turbulence stabilization
Yu Mao, Jerome Gilles
We recently developed a new approach to get a stabilized image from a sequence of frames acquired through atmospheric turbulence. The goal of this algorihtm is to remove the geomet…
Non rigid geometric distortions correction -- Application to atmospheric turbulence stabilization
Yu Mao, Jerome Gilles
A novel approach is presented to recover an image degraded by atmospheric turbulence. Given a sequence of frames affected by turbulence, we construct a variational model to charact…
Multiscale texture separation
Jerome Gilles
In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining th…
Detection and tracking of gas plumes in LWIR hyperspectral video sequence data
Torin Gerhart, Justin Sunu, Ekaterina Merkurjev +3
Automated detection of chemical plumes presents a segmentation challenge. The segmentation problem for gas plumes is difficult due to the diffusive nature of the cloud. The advanta…
Empirical wavelet transform
Jerome Gilles
Some recent methods, like the Empirical Mode Decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful…
Wavelet Burst Accumulation for turbulence mitigation
Jerome Gilles, Stanley Osher
In this paper, we investigate the extension of the recently proposed weighted Fourier burst accumulation (FBA) method into the wavelet domain. The purpose of FBA is to reconstruct…
Open Turbulent Image Set (OTIS)
Nicholas B. Ferrante, Jerome Gilles
Long distance imaging is subject to the impact of the turbulent atmosphere. This results into geometric distortions and some blur effect in the observed frames. Despite the existen…
Bregman implementation of Meyer's norm for cartoon + textures decomposition
Jerome Gilles, Stanley Osher
In this paper, we design a very simple algorithm based on Split Bregman iterations to numerically solve the cartoon + textures decomposition model of Meyer. This results in a signi…
Investigation of moving objects through atmospheric turbulence from a non-stationary platform
Nicholas Ferrante, Jerome Gilles, Shibin Parameswaran
In this work, we extract the optical flow field corresponding to moving objects from an image sequence of a scene impacted by atmospheric turbulence \emph{and} captured from a movi…
Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation
Yuan Huang, Fugen Zhou, Jerome Gilles
In this paper, we propose a new approach to perform supervised texture classification/segmentation. The proposed idea is to feed a Fully Convolutional Network with specific texture…
Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields
Jerome Gilles, Francis Alvarez, Nicholas B. Ferrante +4
In this paper, we investigate how moving objects can be detected when images are impacted by atmospheric turbulence. We present a geometric spatio-temporal point of view to the pro…
Evaluation of neural network algorithms for atmospheric turbulence mitigation
Tushar Jain, Madeline Lubien, Jerome Gilles
A variety of neural networks architectures are being studied to tackle blur in images and videos caused by a non-steady camera and objects being captured. In this paper, we present…
Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets
Yuan Huang, Valentin De Bortoli, Fugen Zhou +1
Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterize different textures. In this paper, we assess the in…
The Empirical Watershed Wavelet
Basile Hurat, Zariluz Alvarado, Jerome Gilles
The empirical wavelet transform is an adaptive multiresolution analysis tool based on the idea of building filters on a data-driven partition of the Fourier domain. However, existi…
Continuous empirical wavelets systems
Jerome Gilles
The recently proposed empirical wavelet transform was based on a particular type of filter. In this paper, we aim to propose a general framework for the construction of empirical w…