Quantification vectorielle

Applied sciences
Information engineering
Traitement du signal
Compression de données

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Publications associées (27)

Geometry-driven quantization for omnidirectional image coding

Pascal Frossard, Francesca De Simone

In this paper we propose a method to adapt the quantization tables of typical block-based transform codecs when the input to the encoder is a panoramic image resulting from equirectangular projection of a spherical image. When the visual content is project ...

2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Distributed wireless video caching placement for dynamic adaptive streaming

Pascal Frossard, Chenglin Li

Caching at edge servers can smooth the temporal traffic variability and reduce the service load of base stations in wireless streaming. However, the assignment of the cached content for possibly multiple versions of different video sequences is still a cha ...

2016

A consensus algorithm for networks with process noise and quantization error

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

In this paper we address the problem of quantized consensus where process noise or external inputs corrupt the state of each agent at each iteration. We propose a quantized consensus algorithm with progressive quantization, where the quantization interval ...

IEEE2015

An efficient initialization mechanism of neurons for Winner Takes All Neural Network implemented in the CMOS technology

Pierre-André Farine, Rafal Tomasz Dlugosz

The paper presents a new initialization mechanism based on a Convex Combination Method (CCM) for Kohonen self-organizing Neural Networks (NNs) realized in the CMOS technology. A proper selection of initial values of the neuron weights exhibits a strong imp ...

Elsevier Science Inc2015

Caching (a pair of) Gaussians

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

A source produces i.i.d. vector samples from a Gaussian distribution, but the user is interested in only one component. In the cache phase, not knowing which component the user is interested in, a first compressed description is produced. Upon learning the ...

2015

Structure Tensor Total Variation

Michaël Unser, Stamatios Lefkimmiatis

We introduce a novel generic energy functional that we employ to solve inverse imaging problems within a variational framework. The proposed regularization family, termed as structure tensor total variation (STV), penalizes the eigenvalues of the structure ...

SIAM2015

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