DEBREUVE , Eric

Statistical similarity measures and k nearest neighbor estimators teamed up to handle high-dimensional descriptors in image and video processing

In emission imaging, nuclear medicine provides functional information about the organ of interest. In transmission imaging, it provides anatomical information whose goal may be the correction of physical phenomena that corrupt emission images. With both emission and transmission images, it is useful to know how to extract, either automatically...

Accurate plankton biomass estimations are essential to study marine ecological processes and biogeochemical cycles. This is particularly truefor copepods, which dominate mesozooplankton. Such estimations can efficiently be computed from organism volume estimated from images.However, imaging devices only provide 2D projections of 3D objects. The...

International audience

National audience

International audience

Accurate plankton biomass estimations are essential to study marine ecological processes and biogeochemical cycles. This is particularly truefor copepods, which dominate mesozooplankton. Such estimations can efficiently be computed from organism volume estimated from images.However, imaging devices only provide 2D projections of 3D objects. The...

This paper deals with region-of-interest (ROI) tracking in video sequences. The goal is to determine in successive frames the region which best matches, in terms of a similarity measure, an ROI defined in a reference frame. Two aspects of a similarity measure between a reference region and a candidate region can be distinguished: radiometry...

International audience

International audience

This paper deals with region-of-interest (ROI) tracking in video sequences. The goal is to determine in successive frames the region which best matches, in terms of a similarity measure, a ROI defined in a reference frame. Some tracking methods define similarity measures which efficiently combine several visual features into a probability...

International audience

International audience

The recent improvements of graphics processing units (GPU) offer to the computer vision community a powerful processing platform. Indeed, a lot of highly-parallelizable computer vision problems can be significantly accelerated using GPU architecture. Among these algorithms, the k nearest neighbor search (KNN) is a well-known problem linked with...

International audience

National audience

Accurate plankton biomass estimations are essential to study marine ecological processes and biogeochemical cycles. This is particularly truefor copepods, which dominate mesozooplankton. Such estimations can efficiently be computed from organism volume estimated from images.However, imaging devices only provide 2D projections of 3D objects. The...

The image restoration problem is addressed in the variational framework. The focus was set on denoising. The statistics of natural images are consistent with the Markov random field principles. Therefore, a restoration process should preserve the correlation between adjacent pixels. The proposed approach minimizes the conditional entropy of a...

Plankton images not only allow to classify organisms taxonomically but also to measure their size, which is then used to estimate their biomass. Accurate plankton biomass estimations are needed to quantify their role in ecological processes and biogeochemical cycles; this is particularly true for copepods, which dominate...

In this paper we address the image restoration problem in the variational framework. The focus is set on denoising applications. Natural image statistics are consistent with a Markov random field (MRF) model for the image structure. Thus in a restoration process attention must be paid to the spatial correlation between adjacent pixels.The...

In this paper we address the image restoration problem in the variational framework. Classical approaches minimize the Lp norm of the residual and rely on parametric assumptions on the noise statistical model. We relax this parametric hypothesis and we formulate the problem on the basis of nonparametric density estimates. The proposed approach...

Patch-based denoising techniques have proved to be very efficient. Indeed, they account for the correlations that exist among the patches of natural images, even when degraded by noise. In this context, we propose a denoising method which tries to minimize over-smoothing of textured areas (an effect observed with NL- means), to avoid staircase...

Recently, patch-based denoising techniques have proved to be very effective. Indeed, they account for the correlations that exist among patches of natural images. Taking a variational approach, we show that the gradient descent for the chosen entropy-based energy leads to a solution involving the mean-shift on patches. Then, we propose a...

In this paper, we define a similarity measure to compare images in the context of (indexing and) retrieval. We use the Kullback-Leibler (KL) divergence to compare sparse multiscale image descriptions in a wavelet domain. The KL divergence between wavelet coefficient distributions has already been used as a similarity measure between images. The...