Marco Dalai

Improving Turbo Codec Integration in Pixel-Domain Distributed Video Coding

The field of distributed video coding (DVC) theory has received a lot of attention in recent years and effective encoding techniques have been proposed. In the present work the framework of pixel domain Wyner-Ziv coding of video frames is considered, following the scheme proposed in A. Aaron et al. (2002). Some key frames are supposed to be available at the decoder while other frames are Wyner-Ziv encoded using turbo codes; at the decoder motion compensated interpolation between the key frames is performed in order to construct the side information for the Wyner-Ziv frame decoding. In this paper an improved model for the correlation noise between the side information frame and the original one is proposed. It is shown that modeling the nonstationary nature of the noise leads to substantial gain in the rate-distortion performance. Furthermore, by considering the memory of the noise, we show that some further gain can be obtained by placing an interleaver before the turbo codec so as to spread the correlation noise all over the frame

Brief paper: Parameter identification for nonlinear systems: Guaranteed confidence regions through LSCR

In this paper we consider the problem of constructing confidence regions for the parameters of nonlinear dynamical systems. The proposed method uses higher order statistics and extends the LSCR (leave-out sign-dominant correlation regions) algorithm for linear systems introduced in Campi and Weyer [2005, Guaranteed non-asymptotic confidence regions in system identification. Automatica 41(10), 1751-1764. Extended version available at ]. The confidence regions contain the true parameter value with a guaranteed probability for any finite number of data points. Moreover, the confidence regions shrink around the true parameter value as the number of data points increases. The usefulness of the proposed approach is illustrated on some simple examples.

A fully scalable video coder with inter-scale wavelet prediction and morphological coding

In this paper a new fully scalable - wavelet based - video coding architecture is proposed, where motion compensated temporal filtered subbands of spatially scaled versions of a video sequence can be used as base layer for inter-scale predictions. These predictions take place between data at the same resolution level without the need of interpolation. The prediction residuals are further transformed by spatial wavelet decompositions. The resulting multi-scale spatiotemporal wavelet subbands are coded thanks to an embedded morphological dilation technique and context based arithmetic coding. Dyadic spatio-temporal scalability and progressive SNR scalability are achieved. Multiple adaptation decoding can be easily implemented without the need of knowing a predefined set of operating points. The proposed coding system allows to compensate some of the typical drawbacks of current wavelet based scalable video coding architectures and shows interesting visual results even when compared with the single operating point video coding standard AVC/H.264.

A new bound on the capacity of the binary deletion channel with high deletion probabilities

Let C(d) be the capacity of the binary deletion channel with deletion probability d. It was proved by Drinea and Mitzenmacher that, for all d, C(d)/(1 − d) ≥ 0.1185. Fertonani and Duman recently showed that lim sup<inf>d→1</inf> C(d)/(1−d) ≤ 0.49. In this paper, it is proved that lim<inf>d→1</inf> C(d)/(1 − d) exists and is equal to inf<inf>d</inf> C(d)/(1−d). This result suggests the conjecture that the curve C(d) my be convex in the interval d ∈ [0, 1]. Furthermore, using currently known bounds for C(d), it leads to the upper bound lim<inf>d→1</inf> C(d)/(1 − d) ≤ 0.4143.

Parametric Identification of Nonlinear Systems: Guaranteed Confidence Regions

In this paper we consider the problem of constructing confidence regions for the parameters of nonlinear dynamical systems. The proposed method makes use of higher order statistics and extends a previous algorithm in [3]. The obtained confidence regions are valid for any finite number of data samples and they are nonconservative, in the sense that they contain the true parameter value with an exact probability. The usefulness of the proposed approach is illustrated in simulation examples. The results presented here are preliminary results from an ongoing research on finite sample properties in nonlinear system identification.

Constant Compositions in the Sphere Packing Bound for Classical-Quantum Channels

The sphere packing bound, in the form given by Shannon, Gallager, and Berlekamp, was recently extended to classical-quantum channels, and it was shown that this creates a natural setting for combining probabilistic approaches with some combinatorial ones such as the Lovász theta function. In this paper, we extend the study to the case of constant-composition codes. We first extend the sphere packing bound for classical-quantum channels to this case, and we then show that the obtained result is related to a variation of the Lovász theta function studied by Marton. We then propose a further extension to the case of varying channels and codewords with a constant conditional composition given a particular sequence. This extension is finally applied to auxiliary channels to deduce a bound, which is useful in the low rate region and which can be interpreted as an extension of the Elias bound.

Sphere packing bound for quantum channels

In this paper, the Sphere-Packing-Bound of Fano, Shannon, Gallager and Berlekamp is extended to general classical-quantum channels. The obtained upper bound for the reliability function, for the case of pure-state channels, coincides at high rates with a lower bound derived by Burnashev and Holevo [1]. Thus, for pure state channels, the reliability function at high rates is now exactly determined. For the general case, the obtained upper bound expression at high rates was conjectured to represent also a lower bound to the reliability function, but a complete proof has not been obtained yet.

Non prefix-free codes for constrained sequences

In this paper we consider the use of variable length non prefix-free codes for coding constrained sequences of symbols. We suppose to have a Markov source where some state transitions are impossible, i.e. the stochastic matrix associated with the Markov chain has some null entries. We show that classic Kraft inequality is not a necessary condition, in general, for unique decodability under the above hypothesis and we propose a relaxed necessary inequality condition. This allows, in some cases, the use of non prefix-free codes that can give very good performance, both in terms of compression and computational efficiency. Some considerations are made on the relation between the proposed approach and other existing coding paradigms

A complex-integration approach to the saddlepoint approximation for random-coding bounds

This paper derives a saddlepoint approximation for the random-coding bound to the error probability of channel coding by using complex-integration techniques. The approximation is given by a sum of two terms: one with Gallagers exponent, and a second one with Arimotos strong converse exponent (above capacity) or the sphere-packing exponent (below the critical rate).

A heuristic for distance fusion in cover song identification

In this paper, we propose a method to integrate the results of different cover song identification algorithms into one single measure which, on the average, gives better results than initial algorithms. The fusion of the different distance measures is made by projecting all the measures in a multi-dimensional space, where the dimensionality of this space is the number of the considered distances. In our experiments, we test two distance measures, namely the Dynamic Time Warping and the Qmax measure when applied in different combinations to two features, namely a Salience feature and a Harmonic Pitch Class Profile (HPCP). While the HPCP is meant to extract purely harmonic descriptions, in fact, the Salience allows to better discern melodic differences. It is shown that the combination of two or more distance measure improves the overall performance.