Publications de Pascal Frossard

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In this article we propose a new super-resolution algorithm tailored for light field cameras, which suffer by design from a limited spatial resolution. To do so, we cast the light field super-resolution problem into an optimization problem, where the parti ...

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

Recently, histopathology foundation models (hFM) have rapidly advanced in size and complexity, achieving excellent performance in cancer diagnosis and biomarker discovery. Here, we specialise pre-trained hFMs to invasive tumour tissue and present three key contributions. First, we systematically evaluate the biological concepts encoded in hFM representations across multiple biological scales. Second, we demonstrate that informed extended pre-training transforms generalist models into tumour-specialised ones

We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by ...

This paper studies quantization error in the context of Matching Pursuit coded streams and proposes a new coefficient quantization scheme taking benefit of the Matching Pursuit properties. The coefficients energy in Matching Pursuit indeed decreases with the iteration number, and the decay rate can be upper-bounded with an exponential curve driven by the redundancy of the dictionary. The redundancy factor is therefore used to design an optimal a posteriori quantization scheme for multi-resolution Matching P

In this paper, we consider the problem of manifold approximation with affine subspaces. Our objective is to discover a set of low dimensional affine subspaces that represent manifold data accurately while preserving the manifold's structure. For this purpose, we employ a greedy technique that partitions manifold samples into groups, which are approximated by low dimensional subspaces. We start by considering each manifold sample as a different group and we use the difference of local tangents to determine a

This paper presents a novel local motion estimation algorithm for omnidirectional images. The algorithm captures correlation between two spherical images of a scene, taken from arbitrary viewpoints, with the objective to reduce the encoding rate of these images. It first performs a multiresolution decomposition of the spherical images, in order to improve the consistency of the motion estimation, with a limited computational complexity. Then, it determines pairs of similar solid angles and matches blocks of

Multiview applications endow final users with the possibility to freely navigate within 3D scenes with minimum-delay. A real feeling of scene navigation is enabled by transmitting multiple high-quality camera views, which can be used to synthesize addition ...

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature attack this problem by distributed linear iterative algorithms, wi ...

The construction of a meaningful graph topology plays a crucial role in the effective representation, processing, analysis, and visualization of structured data. When a natural choice of the graph is not readily available from the data sets, it is thus des ...

We consider the transmission of variable bit rate video over a network offering a guaranteed service such as ATM VBR or the guaranteed service of the IETF. The guaranteed service requires that the flow accepted by the network has to be conforming with a traffic envelope; in return, it receives a service guarantee expressed by a network service curve. In order to satisfy the traffic envelope constraint, the output of the encoder is fed to a smoother, possibly with some look-ahead. The resulting stream is tra

Matching pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a given dictionary. In this paper we focus on the Matching Pursuit representation of the displaced frame difference (dfd). In particular, we introduce a new dictionary for matching pursuit that efficiently exploits the signal structures of the dfd. We also propose a fast strategy to find the atoms exploiting the maximum of the absol

In this paper, we propose a new graph-based coding framework and illustrate its application to image compression. Our approach relies on the careful design of a graph that optimizes the overall rate-distortion performance through an effective graph-based t ...

The paper addresses the media-specific rate allocation problem in multipath networks. The streaming rate on each path is determined such that the end-to-end media distortion is minimized, when the receiving client aggregates packets received via multiple network channels. As it is difficult for the media server to have the full knowledge about the network status, we propose a distributed path selection and rate allocation algorithm. The network nodes participate to the optimization strategy, based on their

This paper addresses the problem of optimal channel rate allocation for media streaming in active networks, where intermediate nodes are able to perform basic FEC decoding/encoding operations. FEC performance is analyzed in the case of hop-by-hop FEC protection, and compared with an end-to-end FEC scenario, in order to demonstrate the benefits of FEC operations in the intermediate nodes. An optimization problem is formulated, based on a distortion model for video streaming over lossy channels. Finally, the

Light field cameras capture the 3D information in a scene with a single exposure. This special feature makes light field cameras very appealing for a variety of applications: from post-capture refocus, to depth estimation and image-based rendering. However ...

This paper addresses the reconstruction of high resolution omnidirectional images from multiple low resolution images with inexact registration. When omnidirectional images from low resolution vision sensors can be uniquely mapped on the 2-sphere, such a r ...

We address the problem of depth and ego-motion estimation from omnidirectional images. We propose a correspondence-free structure from motion problem for images mapped on the 2-sphere. A novel graph-based variational framework is proposed for depth estimation. The problem is cast into a TV-L1 optimization problem that is solved by fast graph-based optimization techniques. The ego-motion is then estimated directly from the depth information without computation of the optical flow. Both problems are addressed

This paper presents an error resilient coding scheme for atomic image bitstreams, as generated by Matching Pursuit encoders. A joint source and channel coding algorithm is proposed, that takes benefit of both the flexibility in the image representation, and the progressive nature of the bitstream, in order to finely adapt the channel rate to the relative importance of the bitstream components. An optimization problem is proposed, and a fast search algorithm determines the best rate allocation for given bit

Pascal Frossard

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A Nonsmooth Graph-Based Approach to Light Field Super-Resolution

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Prognostic RNA-splicing archetypes in breast cancer identified by extended pre-training of histopathology foundation models

Distributed average consensus with quantization refinement

A Posteriori Quantized Matching Pursuit

Tangent-based manifold approximation with locally linear models

Multiresolution Motion Estimation for Omnidirectional Images

Adaptive Streaming in Interactive Multiview Video Systems

Optimal Polynomial Filtering for Accelerating Distributed Consensus

A Variational Framework for Structure from Motion in Omnidirectional Image Sequences

Learning Graphs From Data: A Signal Representation Perspective

Optimal Scheduling of Rich Media in a Rate-Distortion Sense

New Dictionary and Fast Atom Searching Methods for Matching Pursuit Representation of Displaced Frame Difference

Graph-based Transform Coding with Application to Image Compression

Distributed Media Rate Allocation in Multipath Networks

Optimal FEC Rate for Media Streaming in Active Networks

Geometry-Consistent Light Field Super-Resolution via Graph-Based Regularization

Joint registration and super-resolution with omnidirectional images

A Variational Framework for Structure from Motion in Omnidirectional Image Sequences

On the joint source and channel coding of atomic image streams