Béatrice Pesquet-Popescu

RD Optimized Coding for Motion Vector Predictor Selection

The H.264/MPEG4-AVC video coding standard has achieved a higher coding efficiency compared to its predecessors. The significant bitrate reduction is mainly obtained by efficient motion compensation tools, as variable block sizes, multiple reference frames, 1/4-pel motion accuracy and powerful prediction modes (e.g., SKIP and DIRECT). These tools have contributed to an increased proportion of the motion information in the total bit- stream. To achieve the performance required by the future ITU-T challenge, namely to provide a codec with 50% bitrate reduction compared to the current H.264, the reduction of this motion information cost is essential. This paper proposes a competing framework for better motion vector coding and SKIP mode. The predictors for the SKIP mode and the motion vector predictors are optimally selected by a rate-distortion criterion. These methods take advantage from the use of the spatial and the temporal redundancies in the motion vector fields, where the simple spatial median usually fails. An adaptation of the temporal predictors according to the temporal distances between motion vector fields is also described for multiple reference frames and B-slices options. These two combined schemes lead to a systematic bitrate saving on Baseline and High profile, compared to an H.264/MPEG4-AVC standard codec, which reaches up to 45%.

Vector Lifting Schemes for Stereo Image Coding

Many research efforts have been devoted to the improvement of stereo image coding techniques for storage or transmission. In this paper, we are mainly interested in lossy-to-lossless coding schemes for stereo images allowing progressive reconstruction. The most commonly used approaches for stereo compression are based on disparity compensation techniques. The basic principle involved in this technique first consists of estimating the disparity map. Then, one image is considered as a reference and the other is predicted in order to generate a residual image. In this paper, we propose a novel approach, based on vector lifting schemes (VLS), which offers the advantage of generating two compact multiresolution representations of the left and the right views. We present two versions of this new scheme. A theoretical analysis of the performance of the considered VLS is also conducted. Experimental results indicate a significant improvement using the proposed structures compared with conventional methods.

A motion-compensated overcomplete temporal decomposition for multiple description scalable video coding

We present a new multiple-description coding (MDC) method for scalable video, designed for transmission over error-prone networks. We employ a redundant motion-compensated scheme derived from the Haar multiresolution analysis, in order to build temporally correlated descriptions in a t+2D video coder. Our scheme presents a redundancy which decreases with the resolution level. This is achieved by additionally subsampling some of the wavelet temporal subbanbds. We present an equivalent four-band lifting implementation leading to simple central and side decoders as well as a packet-based reconstruction strategy in order to cope with random packet losses.

Side information estimation and new symmetric schemes for multi-view distributed video coding

This paper deals with distributed video coding (DVC) for multi-view sequences. DVC of multi-view sequences is a recent field of research, with huge potential impact in applications such as videosurveillance, real-time event streaming from multiple cameras, and, in general, immersive communications. It raises however several problems, and in this paper we tackle two of them. Based on the principles of Wyner-Ziv (WZ) coding, in multi-view DVC many estimations can be generated in order to create the side information (SI) at the decoder. It has been shown that the quality of the SI strongly influences the global coding performances. Therefore, this paper proposes to study the contribution of multiple SI estimations (in the temporal and view directions) to the global performances. Moreover, we propose new symmetric schemes for longer group of pictures (GOP) in multi-view DVC and show that we can further exploit the long-term correlations using a new kind of estimation, called diagonal. For such schemes, several decoding strategies may be envisaged. We perform a theoretical study of the temporal and inter-view dependencies, and confirm by experiments the conclusion about the best decoding strategy.

Combining Seminorms in Adaptive Lifting Schemes and Applications to Image Analysis and Compression

In this paper, we present some adaptive wavelet decompositions that can capture the directional nature of images. Our method exploits the properties of seminorms to build lifting structures able to choose between different update filters, the choice being triggered by the local gradient-type features of the input. In order to deal with the variety and wealth of images, one has to be able to use multiple criteria, giving rise to multiple choice of update filters. We establish the conditions under these decisions can be recovered at synthesis, without the need for transmitting overhead information. Thus, we are able to design invertible and non-redundant schemes that discriminate between different geometrical information to efficiently represent images for lossless compression methods.

Distributed temporal multiple description coding for robust video transmission

The problem of multimedia communications over best-effort networks is addressed here with multiple description coding (MDC) in a distributed framework. In this paper, we first compare four video MDC schemes based on different time splitting patterns and temporal two- or three-band motion-compensated temporal filtering (MCTF). Then, the latter schemes are extended with systematic lossy description coding where the original sequence is separated into two subsequences, one being coded as in the latter schemes, and the other being coded with a Wyner-Ziv (WZ) encoder. This amounts to having a systematic lossy Wyner-Ziv coding of every other frame of each description. This error control approach can be used as an alternative to automatic repeat request (ARQ) or forward error correction (FEC), that is, the additional bitstream can be systematically sent to the decoder or can be requested, as in ARQ. When used as an FEC mechanism, the amount of redundancy is mostly controlled by the quantization of the Wyner-Ziv data. In this context, this approach leads to satisfactory rate-distortion performance at the side decoders, however it suffers from high redundancy which penalizes the central description. To cope with this problem, the approach is then extended to the use of MCTF for the Wyner-Ziv frames, in which case only the low-frequency subbands are WZ-coded and sent in the descriptions.

Optimization of the predict operator in lifting-based motion-compensated temporal filtering

The motion-compensated temporal filtering is an essential part of a scalable wavelet-based video coding scheme, which applies a temporal wavelet transform in the motion direction over the frames of a video sequence. The lifting structure of the temporal filter bank tackled in this paper involves a predict operator which makes use of two motion vector fields to bidirectionally predict frames from their neighbouring ones. We show in this paper that there exists an optimal algorithm allowing to estimate jointly these two motion vector fields subject to an optimization criterion directly related to the coding of the detail subbands. We provide an iterative suboptimal form of this algorithm implementing this approach. We show that this algorithm provides substantial gains in terms of PSNR, with the same complexity as a separate estimation of the two motion vector fields.

Gradient-driven update lifting for adaptive wavelets

Abstract Over the past few years, wavelets have become extremely popular in signal and image processing applications. The classical linear wavelet transform, however, performs a homogeneous smoothing of the signal contents which, in some cases, is not desirable. This has led to a growing interest in (nonlinear) wavelet representations that can preserve discontinuities, such as transitions and edges. In this paper, we present the construction of adaptive wavelets by means of an extension of the lifting scheme. The basic idea is to choose the update filters according to some decision criterion which depends on the local characteristics of the input signal. We show that these adaptive schemes yield lower entropies than schemes with fixed update filters, a property that is highly relevant in the context of compression . Moreover, we analyze the effect of a scalar uniform quantization and the stability in such adaptive wavelet decompositions.

Temporal scalability through adaptive M-band filter banks for robust H.264/MPEG-4 AVC video coding

This paper presents different structures that use adaptive-band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

Arithmetic coding with adaptive context-tree weighting for the H.264 video coders

We propose applying an adaptive context-tree weighting (CTW) method in the H.264 video coders. We first investigate two different ways to incorporating the CTW method into an H.264 coder and compare the coding effectiveness of using the method with that of using the context models specified in the H.264 standard. We then describe a novel approach for automatically adapting the CTW method based on the syntactic element to be coded and the encoding parameters. We show that our CTW-based arithmetic coding method yields similar or better compression results compared with the context-based adaptive arithmetic coding method used in H.264, without having to specify so many context models.