Section: New Results

Distributed processing and robust communication

Information theory, stochastic modelling, robust detection, maximum likelihood estimation, generalized likelihood ratio test, error and erasure resilient coding and decoding, multiple description coding, Slepian-Wolf coding, Wyner-Ziv coding, information theory, MAC channels

Loss concealment based on video inpainting

Participants : Mounira Ebdelli, Christine Guillemot, Ronan Le Boulch, Olivier Le Meur.

We have developed a loss concealment scheme based on a new hierarchical video examplar-based inpainting algorithm. The problem of loss concealment is to estimate unknown pixels after decoding when the corresponding transport packets have been lost on the transmission network. Before proceeding to the video texture inpainting, the motion vectors of the lost blocks must first be estimated from the motion vectors of the received blocks in the spatial neighborhood. The Motion vectors (MV) of damaged blocks are estimated using a Bilinear Motion Field Interpolation (BMFI) technique.

The algorithm follows a coarse to fine approach and first inpaints a low resolution version of the damaged video. Moving objects, detected thanks to the estimated motion vectors, are processed first. The most similar patches (similar to the known pixels of the patch to be completed) is searched within a motion-compensated window in adjacent frames, and used as an estimate of the pixels to be filled in. Then the static background is inpainted using known co-located pixels of neighboring frames. The remaining holes are filled-in using spatial inpainting.

In a second step, the high frequency details of the inpainted areas are recovered using a super-resolution technique, in the same vein as described in Section 6.2.1 for still images. The inpainted low resolution video is first interpolated using a simple lanczos interpolation. The idea is then to search for the nearest neighbor (the best match) of the interpolated version of each inpainted block, within the known part of the current image of the impaired video at the native resolution. The found correspondences form a so-called nearest neighbor field (NNF) which connects inpainted and interpolated patches of the low resolution video to high resolution patches of known parts of the high resolution (HR) video. The found NN patch is then copied to replace the low resolution inpainted patch.The two-step approach allows significantly reducing the execution time of the video inpainting process, while preserving a satisfactory quality.

Universal distributed coding

Participant : Aline Roumy.

In 2012, we started a new collaboration with Michel Kieffer and Elsa Dupraz (Supelec, L2S) on universal distributed source coding. Distributed source coding refers to the problem where several correlated sources need to be compressed without any cooperation at the encoders. Decoding is however performed jointly. This problem arises in sensor networks but also in video compression techniques, where the correlation between the successive frames is not directly used at the encoder, and are therefore seen as distributed. Traditional approaches (from an information theoretical but also practical point of view) assume that the correlation channel between the sources is perfectly known. Since this assumption is not satisfied in practice, a way to get around this is to use a feedback channel (from the decoder to the encoder), that can trigger the encoder.

Instead, we consider universal distributed source coding, where the correlation channel is unknown and belongs to a class parametrized by some unknown parameter vector. We proposed four uncertainty models that depend on the partial knowledge we have on the correlation channel and derived the information theoretical bounds [28] . A complete coding scheme has also been proposed that works well for any distribution in the class [27] . At the encoder, the proposed scheme encompasses the determination of the coding rate and the design of the encoding process. Both contributions result from the information-theoretical compression bounds of universal lossless source coding with side information. Then a novel decoder is proposed that takes into account the available information regarding the class. The proposed scheme avoids the use of a feedback channel or the transmission of a learning sequence, which both would result in a rate increase at finite length.