The heterogeneous nature of modern communications stems from the need of transmitting digital information through
various types of mediums to a large variety of end-user terminals. In this context, simultaneously providing a scalable
source representation and resilience against transmission errors is of primary importance. MESHGRID, which is part of
the MPEG-4 AFX standard, is a scalable 3D object representation method especially designed to address the
heterogeneous nature of networks and clients in modern communication systems. A MESHGRID object comprises one or
several surface layers attached to and located within a volumetric reference-grid. In this paper we focus on the errorresilience
aspects of MESHGRID and propose a novel approach for scalable error-resilient coding of MESHGRID's
reference-grid. An unequal error protection approach is followed, to acquaint for the different error-sensitivity levels
characterizing the various resolution and quality layers produced by the reference-grid coder. The code rates to be
employed for each layer are determined by solving a joint source and channel coding problem. The L-infinite distortion
metric is employed instead of the classical L-2 norm, typically used in case of images and video. In this context, a novel
fast algorithm for solving the optimization problem is proposed. The proposed approach allows for real-time
implementations. The experimental results demonstrate the benefits brought by error resilient coding of the reference
grid. We conclude that the proposed approach offers resilience against transmission errors while preserving all the
scalability features and animation capabilities that characterize MESHGRID.
The transmission of images over heterogeneous networks to a large variety of terminals induces the need for efficient scalable image coding, and adapted error control mechanisms to protect the compressed bit stream against degradations caused by packet losses. In this context, we propose an optimal joint source channel coding (JSCC) approach combined with unequal error protection (UEP) of the transmitted data packets enabling an error-resilient transmission of embedded wavelet-based coded images over binary erasure channels. We theoretically show that the average expected rate-distortion function of the separately encoded subbands is convex with monotonically decreasing slopes and prove that a similar conclusion with bounds on the allowable code rates can be drawn when transmitting an increasing number of fixed-length packets. Based on these proofs we conclude that the developed JSCC-allocation process can rely on a Lagrangian-multiplier method. In order to reduce the computational complexity of the allocation mechanism, we propose a novel Viterbi-based search-algorithm, which determines for every subband the near-optimum number of packets and their corresponding code-rates. We show that our proposed solution results in significant complexity reductions while providing very near-to-optimal performance. The experimental results show that when the channel estimation matches the real channel that the use of UEP can deliver significantly better results than the use of EEP.
Error protection and concealment of motion vectors are of prime concern when video is transmitted over variable-bandwidth error-prone channels, such as wireless channels. In this paper, we investigate the influence of corrupted motion vectors in video coding based on motion-compensated temporal filtering, and develop various error protection and concealment mechanisms for this class of codecs. The experimental results show that our proposed motion vector coding technique significantly increases the robustness against transmission errors and generates performance gains of up to 7 dB compared with the original coding technique at the cost of less than 4% in terms of rate. It is also shown that our proposed spatial error-concealment mechanism leads to additional performance gains of up to 4 dB.