Abstract: An important issue with oversampled FIR analysis filter banks (FBs) is to determine inverse synthesis FBs, when they exist. Given any complex oversampled FIR analysis FB, we first provide an algorithm to determine whether there exists an inverse FIR synthesis system. We also provide a method to ensure the Hermitian symmetry property on the synthesis side, which is serviceable to processing real-valued signals. As an invertible analysis scheme corresponds to a redundant decomposition, there is no unique inverse FB. Given a particular solution, we parameterize the whole family of inverses through a null space projection. The resulting reduced parameter set simplifies design procedures, since the perfect reconstruction constrained optimization problem is recast as an unconstrained optimization problem. The design of optimized synthesis FBs based on time or frequency localization criteria is then investigated, using a simple yet efficient gradient algorithm.

Abstract: The use of multicomponent images has become widespread with the improvement of multisensor systems having increased spatial and spectral resolutions. However, the observed images are often corrupted by an additive Gaussian noise. In this paper, we are interested in multichannel image denoising based on a multiscale representation of the images. A multivariate statistical approach is adopted to take into account both the spatial and the intercomponent correlations existing between the different wavelet subbands. More precisely, we propose a new parametric nonlinear estimator which generalizes many reported denoising methods. The derivation of the optimal parameters is achieved by applying Stein's principle in the multivariate case. Experiments performed on multispectral remote sensing images clearly indicate that our method outperforms conventional wavelet denoising techniques.

Abstract: Comprehensive two-dimensional gas chromatography (GCxGC) is a major advance for the detailed characterisation of petroleum products. This technique is based on two orthogonal dimensions of separation achieved by two chromatographic capillary columns of different chemistries and selectivities. High-frequency sampling between the two columns is achieved by a modulator, ensuring that the whole sample is transferred and analysed continuously in both separations. Thus, the peak capacity and the resoluting power dramatically increase. Besides, highly structured 2D chromatograms are obtained upon the volatility and the polarity of the solute to provide more accurate molecular identification of hydrocarbons. In this paper fundamental and practical considerations for implementation of GCxGC are reviewed. Selected applications obtained using a prototype of a GCxGC chromatograph developed in-house highlight the potential of the technique for molecular characterisation of middle distillates, sulphur speciation in diesel and analysis of effluents front petrochemical processes.

Abstract: Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced redundancy. When the decomposition of a random process is performed-which occurs in particular when an additive noise is corrupting the signal to be analyzed-it is useful to characterize the statistical properties of the dual-tree wavelet coefficients of this process. As dual-tree decompositions constitute overcomplete frame expansions, correlation structures are introduced among the coefficients, even when a white noise is analyzed. In this paper, we show that it is possible to provide an accurate description of the covariance properties of the dual-tree coefficients of a wide-sense-stationary process. The expressions of the (cross-) covariance sequences of the coefficients are derived in the one and two-dimensional cases. Asymptotic results are also provided, allowing to predict the behavior of the second-order moments for large lag values or at coarse resolution. In addition, the cross-correlations between the primal and dual wavelets, which play a primary role in our theoretical analysis, are calculated for a number of classical wavelet families. Simulation results are finally provided to validate these results.

Abstract: We propose a two-dimensional generalization to the M-band case of the dual-tree decomposition structure (initially proposed by Kingsbury and further investigated by Selesnick) based on a Hilbert pair of wavelets. We particularly address: 1) the construction of the dual basis and 2) the resulting directional analysis. We also revisit the necessary pre-processing stage in the M-band case. While several reconstructions are possible because of the redundancy of the representation, we propose a new optimal signal reconstruction technique, which minimizes potential estimation errors. The effectiveness of the proposed M-band decomposition is demonstrated via denoising comparisons on several image types (natural, texture, seismics), with various M-band wavelets and thresholding strategies. Significant improvements in terms of both overall noise reduction and direction preservation are observed.

Abstract: The detailed characterisation of middle distillates is essential for a better understanding of reactions involved in refining process. Owing to higher resolution power and enhanced sensitivity, comprehensive two-dimensional gas chromatography (GC x GC) is a powerful tool for improving characterisation of petroleum samples. The aim of this paper is to compare GC x GC and various ASTM methods - gas chromatography (GC), liquid chromatography (LC) and mass spectrometry (MS) - for group type separation and detailed hydrocarbon analysis. Best features of GC x GC are demonstrated and compared to these techniques in terms of cost, time consumption and accuracy. In particular, a new approach of simulated distillation (SimDis-GC x GC) is proposed: compared to the standard method ASTM D2887 it gives unequal information for better understanding of conversion process. (c) 2005 Elsevier B.V. All rights reserved.

Abstract: Seismic exploration provides information about the ground substructures. Seismic images are generally corrupted by several noise sources. Hence, efficient denoising procedures are required to improve the detection of essential geological information. Wavelet bases provide sparse representation for a wide class of signals and images. This property makes them good candidates for efficient filtering tools, allowing the separation of signal and noise coefficients. Recent works have improved their performance by modelling the intra- and inter-scale coefficient dependencies using hidden Markov models, since image features tend to cluster and persist in the wavelet domain. This work focuses on the use of lapped transforms associated with hidden Markov modelling. Lapped transforms are traditionally viewed as block-transforms, composed of M pass-band filters. Seismic data present oscillatory patterns and lapped transforms oscillatory bases have demonstrated good performances for seismic data compression. A dyadic like representation of lapped transform coefficient is possible, allowing a wavelet-like modelling of coefficients dependencies. We show that the proposed filtering algorithm often outperforms the wavelet performance both objectively (in terms of SNR) and subjectively: lapped transform better preserve the oscillatory features present in seismic data at low to moderate noise levels.

Abstract: Comprehensive two-dimensional gas chromatography (GC x GC) has been investigated for the characterization of high valuable petrochemical samples from dehydrogenation of n-paraffins, Fischer-Tropsch and oligomerization processes. GC x GC separations, performed using a dual-jets CO2 modulator, were optimized using a test mixture representative of the hydrocarbons found in petrochemicals. For complex samples, a comparison of GC x GC qualitative and quantitative results with conventional gas chromatography (ID-GC) has demonstrated an improved resolution power of major importance for the processes: the group type separation has permitted the detection of aromatic compounds in the products from dehydrogenation of n-paraffins and from oligomerization, and the separation of alcohols from other hydrocarbons in Fischer-Tropsch products. (C) 2004 Published by Elsevier B.V.