Marie Andrée Agostini

Improving H.264 performances by quantization of motion vectors

The coding resources used for motion vectors (MVs) can attain quite high ratios even in the case of efficient video coders like H.264, and this can easily lead to suboptimal rate-distortion performance. In a previous paper, we proposed a new coding mode for H.264 based on the quantization of motion vectors (QMV). We only considered the case of 16x16 partitions for motion estimation and compensation. That method allowed us to obtain an improved trade-off in the resource allocation between vectors and coefficients, and to achieve better rate-distortion performances with respect to H.264. In this paper, we build on the proposed QMV coding mode, extending it to the case of macroblock partition into smaller blocks. This issue requires solving some problems mainly related to the motion vector coding. We show how this task can be performed efficiently in our framework, obtaining further improvements over the standard coding technique.

Motion Vector Quantization for Efficient Low Bit-rate Video Coding

The most recent video coding standard H.264 achieves excellent compression performances at many different bit-rates. However, it has been noted that, at very high compression ratios, a large part of the available coding resources is only used to code motion vectors. This can lead to a suboptimal coding performance. This paper introduces a new coding mode for a H.264-based video coder, using quantized motion vector (QMV) to improve the management of the resource allocation between motion information and transform coeffcients. Several problems have to be faced with in order to get an efficient implementation of QMV techniques, yet encouraging results are reported in preliminary tests, allowing to improve the performances of H.264 at low bit-rates over several sequences.

Theoretical Model of the Coding Error in MCWT Video Coders

In motion-compensated wavelet based video coders (MCWT), it is known that a precise motion estimation is necessary to minimize the wavelet coefficients energy. However, a motion vectors field of high precision is expensive in binary resources compared to the wavelet subbands. In order to reduce the quantity of bits required to represent these vectors, we proposed in a previous work to quantize the motion vectors using a scalable and open-loop lossy coder, while controlling the rate-distortion trade-off. Obviously, this lossy motion coding has an impact on the decoded sequence. In this paper, we propose to evaluate this impact by establishing a theoretical distortion model of motion coding error, including also the subbands quantization noise. This model will allow to realize an optimal model-based bit-rate allocation between wavelet coefficients and motion information. Experimental validation of the model gives interesting results.

Efficient Frame Interpolation for Wyner-Ziv Video Coding

In the framework of Wyner-Ziv Coding of Video, the coding efficiency depends on the quality of the side information (SI) at the decoder, where the side information is constructed from the key frames available at the decoder. In this paper, we propose a novel frame interpolation method for Wyner-Ziv coding, where the motion compensation is bidirectional and allows pixelwise estimation. The proposed interpolation method allows to obtain better SI quality than the one obtained by state-of-the-art interpolation methods.

Map estimation of multiple description encoded video transmitted over noisy channels

The problem of efficient video transmission over noisy channels involves high compression rates and robustness to channel errors. In the framework of multiple description coding (MDC), we focus on the direct estimation of the source from two noisy descriptions, without trying to estimate the single descriptions. The challenge is to reconstruct a central signal with distortion as small as possible using the knowledge of the two noisy descriptions. We propose in this paper a maximum a posteriori (MAP) estimator for the decoding of the central description, using the knowledge of the probability density function (pdf) of the different subband descriptions. The balanced MDC scheme used for application is a scan-based wavelet transform video coding scheme, and includes an efficient bit allocation procedure that dispatches the source video redundancy between the different descriptions, depending on the characteristics of the channel. Simulation results show a good robustness of the proposed decoding scheme against transmission errors, with an improvement of 2 dB in PSNR compared to a maximum likelihood (ML) technique.

Modeling the Motion Coding Error for Mcwt Video Coders

In motion-compensated wavelet based video coders, a very precise motion estimation is necessary. However, a motion vectors field of high precision is expensive in binary resources and requires a great place in the bitstream compared to the wavelet coefficients. Thus, we need to reduce the cost of the motion information. To this end, we propose an approach based on a scalable lossy coding of high-precision motion vectors. It allows to optimize the trade-off between motion bit-rate and wavelet coefficients bit-rate, strongly reduces the motion cost, and thus, increases the coder performances at low bit-rate. Obviously, this lossy motion coding has an impact on the decoded sequence. In this paper, we evaluate this impact by establishing a theoretical distortion model for the motion coding error. This model allows the realization of an optimal model-based bit-rate allocation between wavelet subbands and motion vectors. The experimental validation of the model gives satisfactory results