Today's the paradigm for video compression has been significant development represented by the emergence of an important number of international standards efforts of ITU-TVCEG and ISO-IEC MPEG. The main objective of the current systems (such as the standards of MPEG-X and H-E6X) is to compress the original information in order to reduce the transmission rate.

In this paper, we propose a novel acoustic indoor localization system that is based on time reversal. The system estimates the target position with different precision. First, it uses a low frequency signal in order to localize the source in the whole area within coarse precision. Then, it switches to high frequency signal to estimate the target location in a reduced area within a fine precision. The system performance have been evaluated by simulations and by experiments conducted in a practical training room in the National School of Engineers of Le Mans. Results have shown that the system has subcentimeter accuracy.

In this paper, we propose a novel acoustic localization system based on fingerprinting technique. It deploys the Time Of Arrival of CDMA signals emitted by speakers to locate a microphone. The system is inspired from our earlier proposed scheme [1] which deploys the lateration method. Here, we adopt the fingerprinting technique since it is more applicable to indoor environments. The position estimation is accomplished through nonparametric kernel regression. Performance are evaluated by experiments, performed in a hall of interns in National School of Engineers of Le Mans. Results have shown that our proposed scheme provides an accuracy of 8.5 cm within 80% precision.

Most source coding standards (voice, audio, image and video) use Variable-Length Codes (VLCs) for compression. However, the VLC decoder is very sensitive to transmission errors in the compressed bit-stream. Previous contributions, using a trellis description of the VLC codewords to perform soft decoding, have been proposed. Significant improvements are achieved by this approach when compared with prefix decoding. Nevertheless, for realistic VLCs, the complexity of the trellis technique becomes intractable. In this paper, we propose a soft-input VLC decoding method using an a priori knowledge of the lengths of the source-symbol sequence and the compressed bit-stream with Maximum A Posteriori (MAP) sequence estimation. Performance in the case of transmission over an Additive White Gaussian Noise (AWGN) channel is evaluated. Simulation results show that the proposed decoding algorithm leads to significant performance gain in comparison with the prefix VLC decoding besides exhibiting very low complexity. A new VLC decoding method generating additional information regarding the reliability of the bits of the compressed bit-stream is also proposed. We consider the serial concatenation of a VLC with two types of channel code and perform iterative decoding. Results show that, when concatenated with a recursive systematic convolutional code (RSCC), iterative decoding provides remarkable error correction performance. In fact, a gain of about 2.3 dB is achieved, in the case of transmission over an AWGN channel, with respect to tandem decoding. Second, we consider a concatenation with a low-density parity-check (LDPC) code and it is shown that iterative joint source/channel decoding outperforms tandem decoding and an additional coding gain of 0.25 dB is achieved.

The application of distributed coding in many media applications, where low power and low-complexity encoder device is essential, is a new paradigm. In this paper, we propose a new pixel-domain Distributed Video Coding (DVC) scheme, in which both temporal and spatial correlations are exploited at the decoder. The Slepian-Wolf decoder is modified by introducing a source decoder to exploit Wyner-Ziv frame's spatial correlation. We assume the most significant bitplanes to be one-dimensional stationary markov process. The markov characteristic means that this source has a residual redundancy providing additional information for the receiver and can be exploited to correct some errors introduced by the virtual channel, through a joint source-channel decoding scheme.

In this paper a novel joint source channel (JSC) decoding technique is presented. The proposed approach enables iterative decoding for serially concatenated arithmetic codes and convolutional codes. Iterations are performed between Soft In Soft Out (SISO) component decoders. For arithmetic decoding, we proposed to employ a low complex trellis search technique to estimate the best transmitted codewords and generate soft outputs. Performance of the presented system are evaluated in terms of PER, in the case of transmission across the AWGN channel. Simulation results show that the proposed JSC iterative scheme leads to significant gain in comparison with a traditional separated decoding. Finally, the practical relevance of the proposed technique is validated under an image transmission system using the SPIHT codec.

In this paper we propose an image coding scheme based on Block Turbo Codes (BTC) for protecting SPIHT coded images transmitted over wireless channels. An Unequal Error Protection (UEP) scheme using different product codes is also presented. The optimization of the UEP scheme under a transmission budget constraint is investigated. Performance of the proposed system are first evaluated over Gilbert-Elliott (GE) channels. They are then compared to the well-known system of Sherwood and Zeger, through numerical simulations over a single path Rayleigh fading channel. Then, we present an optimized mobile image transmission framework involving a multiuser asynchronous DS-CDMA transmission system over Rayleigh multipath channels. Simulation results for the 512x512 Lena image, transmitted over the ITU Vehicular A channel, show that a significant gain in PSNR is obtained by using the SIC/RAKE multiuser detector in comparison with a conventional detection by the RAKE receiver. Furthermore, performance are also improved when introducing the UEP scheme.

We propose an optimized coding system for progressive image transmission. This system includes a robust image compression algorithm based on the SPIHT (set partitioning in hierarchical trees) coder. Previous work has shown that with a small amount of extra redundancy, we can integrate error detection into arithmetic coding. This technique is used to provide error detection and to improve the channel decoder performance (list Viterbi algorithm: LVA) by means of a joint source channel decoding scheme. Moreover, an unequal error protection (UEP) method which applies error detection coding only to bits affected by error propagation is introduced. Simulations on binary symmetric channels with bit error probabilities of 1.2/spl times/10/sup -1/ and 2/spl times/10/sup -2/, for the 512/spl times/512 Lena image at a source coding bit rate of 1 bpp, show that significant improvement in terms of packet recovery rates and PSNR can be obtained with the proposed system in comparison with the well-known system presented by Sherwood and Zeger (1997).