C. Guillemot

Institut National de Recherche en Informatique et Automatique (INRIA), Sirocco team, Faculty Member

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Papers by C. Guillemot

Overlapped Arithmetic Codes With Memory

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008

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Sparse Representation For Image Prediction

Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007

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Representing Laplacian Pyramids With Varying Amount Of Redundancy

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 2006

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Data-rate constrained lattice vector quantization: a new quantizing algorithm in a rate-distortion sense

Proceedings., International Conference on Image Processing

... Patrice ONNO and Christine GUILLEMOT CCETT 4, rue du Clos Courtel 35 512 Cesson-Sdvignd - FRA... more

Image coding with iterated contourlet and wavelet transforms

2004 International Conference on Image Processing, 2004. ICIP '04.

This paper presents a new coding technique based on a mixed contourlet and wavelet transform. The... more This paper presents a new coding technique based on a mixed contourlet and wavelet transform. The redundancy of the transform is controlled by using the contourlet at fine scales and by switching to a separable wavelet transform at coarse scales. The transform is then optimized through an iterative projection process in the transform domain in order to minimize the quantization error in the image domain. A gain of respectively up to 0.5dB and to 1 dB over respectively contourlet and wavelet based coding has been observed for images with directional features.

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Rate-adaptive codes for the entire Slepian-Wolf region and arbitrarily correlated sources

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008

In this paper, we focus on the design of distributed source codes that can achieve any point in t... more In this paper, we focus on the design of distributed source codes that can achieve any point in the Slepian-Wolf (SW) region and at the same time adapt to any correlation between the sources. A practical solution based on punctured accumulated LDPC codes extended to the non asymmetric case is described. The approach allows flexible rate allocation to the two sources with a gap of 0.0677 bits with respect to the minimum achievable rate.

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Non-asymmetric Slepian-Wolf coding of non-uniform Bernoulli sources

2010 6th International Symposium on Turbo Codes & Iterative Information Processing, 2010

We address the problem of non-asymmetric Slepian-Wolf (SW) coding of two correlated non-uniform B... more We address the problem of non-asymmetric Slepian-Wolf (SW) coding of two correlated non-uniform Bernoulli sources. We first show that the problem is not symmetric in the two sources, contrarily to the case of uniform sources, due to the asymmetry induced by two underlying channel models, namely additive and predictive Binary Symmetric Channels (BSC). That asymmetry has to be accounted for during the decoding. In view of that result, we describe the implementation of a joint nonasymmetric decoder of the two sources based on Low-Density Parity-Check (LDPC) codes and Message Passing (MP) decoding. We also give a necessary and sufficient condition for the recovery of the two sources, that imposes a triangular structure of a subpart of the equivalent matrix representation of the code.

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Hidden Markov Model for distributed video coding

2010 IEEE International Conference on Image Processing, 2010

This paper addresses the problem of asymmetric distributed coding of correlated binary Hidden Mar... more This paper addresses the problem of asymmetric distributed coding of correlated binary Hidden Markov Sources, modeled as a Gilbert-Elliott process. The model parameters are estimated with an estimation-decoding Expectation-Maximization algorithm. The rate gain obtained by accounting for the memory of the sources is first assessed theoretically. The method is then shown to improve the PSNR versus rate performance of a Distributed Video Coding system, based on Low-Density Parity-Check codes.

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Mesh-Based Motion-Compensated Interpolation for Side Information Extraction in Distributed Video Coding

2006 International Conference on Image Processing, 2006

This paper addresses the problem of side information generation in distributed video compression ... more This paper addresses the problem of side information generation in distributed video compression (DVC) schemes. Intermediate frames constructed by motioncompensated interpolation of key frames are used as side information to decode Wyner-Ziv frames. The limitations of block-based translational motion models call for new motion models. This article studies the benefits of meshbased motion-compensated (MC) interpolation for side information extraction in DVC. A hybrid block-based and mesh-based solution addressing the problem of motion discontinuities and occlusions is also described. The increased correlation between the side information and the Wyner-Ziv encoded frames leads to performance gains which can reach up to 1 dB with respect to block-based solutions.

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Locally linear embedding based texture synthesis for image prediction and error concealment

2012 19th IEEE International Conference on Image Processing, 2012

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HEVC Intra coding of ultra HD video with reduced complexity

2014 IEEE International Conference on Image Processing (ICIP), 2014

The HEVC (High Efficiency Video Coding) standard brings the necessary quality versus rate perform... more The HEVC (High Efficiency Video Coding) standard brings the necessary quality versus rate performance for efficient transmission of Ultra High Definition formats (UHD). However, one of the remaining barriers to its adoption for UHD content is its high encoding complexity. In this paper, we address the problem of HEVC encoding complexity reduction by proposing a strategy to infer UHD coding modes and quadtree structure from those optimized for the lower (HD) resolution version of the input video. A speed-up factor of 3 is achieved compared to directly encoding the UHD format at the expense of a limited quality loss.

Fast implementation of a l∞- l/1 penalized sparse representations algorithm: applications in image denoising and coding

Sparse representation techniques have become an important tool in image processing in recent year... more Sparse representation techniques have become an important tool in image processing in recent years, for coding, de-noising and in-painting purposes, for instance. They generally rely on an©-¨¦ penalized criterion and fast algorithms have been proposed to speed up the applications. We propose to replace the¨©-part of the criterion, which has been chosen both for its easy implementation and its relation to the PSNR quality measure, by ä ¡-part. We present a new fast way to minimize a¨¡-¦ penalized criterion and assess its potential benefits for image De-noising and coding.

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Image compression using the Iteration-Tuned and Aligned Dictionary

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011

We present a new, block-based image codec based on sparse representations using a learned, struct... more We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the Iteration-Tuned and Aligned Dictionary (ITAD). The question of selecting the number of atoms used in the representation of each image block is addressed with a new, global (image-wide), rate-distortion-based sparsity selection criterion. We show experimentally that our codec outperforms JPEG2000 in both quantitative evaluations (by 0.9 dB to 4 dB) and qualitative evaluations.

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K-NN search using local learning based on regression for neighbor embedding-based image prediction

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013

ABSTRACT The paper describes a K-NN search method aided by local learning of subspace mappings fo... more ABSTRACT The paper describes a K-NN search method aided by local learning of subspace mappings for the problem of neighbor-embedding based image Intra prediction. The local learning of subspace mappings relies on multivariate linear regression. The method is used jointly with Locally Linear Embedding (LLE) as well as with a method inspired from Non Local Means (NLM) for prediction. Linear and kernel ridge regression are also considered directly for predicting the unknown pixels. Rate-distortion performances are then given in comparison with Intra prediction using LLE and classical K-NN search, as well as in comparison with H.264 Intra prediction modes.

Optimal Inverse Quantisation in Wyner-Ziv Video Coding with Multiple Side Information

International audienceNo abstrac

3D-CE5. h: Reducing the coding cost of merge index by dynamic merge index re-allocation

HEVC implements a candidate vector list for merge and skip modes. When merge or skip modes are se... more HEVC implements a candidate vector list for merge and skip modes. When merge or skip modes are selected, a merge index is written in the bitstream. This index is first binarized using a unary code, then CABAC encoded. A CABAC context is dedicated to the first bin of the unary coded index while the remaining bins are considered as equiprobable. This strategy is efficient as long as the candidate list is constructed such as being ordered by decreasing index occurrence probability. In the context of 3D video encoding, an interview motion vector predictor is added at the first position of the candidate list. It is reported in this document that the interview motion vector predictor is not always the most probable candidate. It actually depends on the video sequence characteristics. Therefore, a dynamic candidate vector list ordering is proposed. Coding gains of 0.4 % on average are observed on side views and up to 1.0% is attained for the Ghost Town Fly sequence for both side views.

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Représentations parcimonieuses par un dictionnaire à structure adaptative: application au codage d'images satellitaires

Dans un contexte de codage d'images satellitaires, une structure de dictionnaire adaptative est a... more Dans un contexte de codage d'images satellitaires, une structure de dictionnaire adaptative est apprise afin de représenter les données de façon parcimonieuse tout en optimisant le compromis entre l'erreur d'approximation et le coût de codage. Cette nouvelle structure de dictionnaire, dite en "cerf-volant", s'adapte aux données d'apprentissage et peut être considérée comme une évolution d'une structure en arbre. Une méthode de sélection des atomes au sein de cette structure, appelée Sélection Adaptative des Atomes par Niveau (SAAN), est également présentée. Elle permet de sélectionner un ou plusieurs atomes par niveau selon un critère de qualité de la représentation. Un gain en débit-distorsion est observé pour la structure en "cerf-volant" par rapport aux dictionnaires dits "plats" (K-SVD, DCT) et par rapport à une structure arborescente, dont les niveaux sont de plus en plus vides et donc de moins en moins efficaces.

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Compact and coherent dictionary for example-based super-resolution

Depth Coding

Punctured Quasi-Arithmetic Codes for Distributed Source Coding

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