An adaptive Gaussian model for satellite image deblurring

The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the reconstructed solution. Since real satellite data show spatially variant characteristics, we propose here to use an inhomogeneous model. We use the maximum likelihood estimator (MLE) to estimate its parameters and we show that the MLE computed on the corrupted image is not suitable for image deconvolution because it is not robust to noise. We then show that the estimation is correct only if it is made from the original image. Since this image is unknown, we need to compute an approximation of sufficiently good quality to provide useful estimation results. Such an approximation is provided by a wavelet-based deconvolution algorithm. Thus, a hybrid method is first used to estimate the space-variant parameters from this image and then to compute the regularized solution. The obtained results on high resolution satellite images simultaneously exhibit sharp edges, correctly restored textures, and a high SNR in homogeneous areas, since the proposed technique adapts to the local characteristics of the data.     

Effects of the smoking process on odour characteristics of smoked herring (Clupea harengus) and relationships with phenolic compound content

The relationship between smoking parameters and odour characteristics, evaluated by a trained sensory panel, were studied on smoked herring. In addition, a possible correlation between the content of 10 phenolic compounds and sensory perceptions was investigated. Five smoking techniques were applied, combining smoke production conditions, performed by pyrolysis of beech wood sawdust or by friction of beech wood log, with smoke deposition, either in a controlled kiln (traditional smoking) or by an electrostatic process. In the fifth smoking technique, a purified condensate of beech smokes was vaporised on fish fillets in the smokehouse. The time of smoking was 3 h for traditional smoking and the liquid smoke atomisation process and 12 min for the electrostatic method. The effects of three smoking temperatures (16, 24, 32 °C) were tested for both the traditional and the liquid smoke atomisation processes, as well as the effect of the position of the exhaust valve in the smokehouse in the case of the traditional method. Two different voltages were applied for the electrostatic process, 37 and 42 kV.     

Generalized sampling: stability and performance analysis

Generalized sampling provides a general mechanism for recovering an unknown input function f(x)ϵℋ from the samples of the responses of m linear shift-invariant systems sampled at 1/mth the reconstruction rate. The system can be designed to perform a projection of f(x) onto the reconstruction subspace V(φ)=span {φ(x-k)}_kϵZ; for example, the family of bandlimited signals with φ(x)=sinc(x). This implies that the reconstruction will be perfect when the input signal is included in V(φ): the traditional framework of Papoulis' (1977) generalized sampling theory. Otherwise, one recovers a signal approximation f(x)ϵV(φ) that is consistent with f(x) in the sense that it produces the same measurements. To characterize the stability of the algorithm, we prove that the dual synthesis functions that appear in the generalized sampling reconstruction formula constitute a Riesz basis of V(φ), and we use the corresponding Riesz bounds to define the condition number of the system. We then use these results to analyze the stability of various instances of interlaced and derivative sampling. Next, we consider the issue of performance, which becomes pertinent once we have extended the applicability of the method to arbitrary input functions, that is, when ℋ is considerably larger than V(φ), and the reconstruction is no longer exact. We show that the generalized sampling solution is essentially equivalent to the optimal minimum error approximation. We then perform a detailed analysis for the case in which the analysis filters are in L₂ and determine all relevant bound constants explicitly. Finally, we use an interlaced sampling example to illustrate these various calculations     

Effect of the doping time of the 1‐butyl‐3‐methylimidazolium ionic liquid cation on the Nafion membrane proprieties

Nafion membranes were prepared by incorporating in the polymer matrix the 1‐butyl‐3‐methylimidazolium (BMI⁺) ionic liquid cation at different doping levels. Increasing the doping time of the membranes with the ionic liquid results in increased incorporation of the BMI⁺ cation but a decrease in the bulk conductivity. The thermogravimetric analysis shows that the BMI⁺ cation incorporation increases the thermal stability of the membranes. The higher discharge efficiency of the fuel cell at 80°C was obtained by using Nafion membrane after 15 minutes of doping in the ionic liquid solution.     

Increasing temporal resolution of DSC perfusion MRI using the analytic image concept

Object  

Dynamic susceptibility contrast MRI (DSC-MRI) is increasingly being used to evaluate cerebral microcirculation. In this study, the use of the analytic image reconstruction (AIR), with the aim to increase the temporal resolution, is evaluated for DSC-MRI in small animals.     

pH-metric study of the setting reaction of monocalcium phosphate monohydrate/calcium oxide-based cements

Hydraulic calcium phosphate cements (CPCs) that are used as osseous substitutes, set by an acid–base reaction between an acid calcium phosphate and a basic calcium salt (often a phosphate). In order to gain a better understanding of the setting of the monocalcium phosphate monohydrate–calcium oxide cement that we developed and in the aim to improve its mechanical properties, the setting reaction was studied by pH-metry. The two methods described in the literature were used. In the first, cement samples were prepared then crushed after different storage periods at 37 °C, 100% RH. The powder was then immersed in pure water with stirring and the pH was measured after equilibration. In the second technique, the starting materials were poured into water while stirring and the pH were followed over time. The two methods gave different results. The first procedure provided information concerning the pH of the surrounding liquid following the partial dissolution of the cement components, rather than any information about pH changes during setting. The second method is more appropriate to follow the pH variations during setting. In this second procedure, the effects of different parameters such as crushing time, stirring rate, liquid-to-powder (L/P) ratio and temperature were investigated. These parameters may impact substantially on the shape and position of the pH=f(t) curves. One or three pH jumps were observed during the setting depending on the composition of the liquid phase. The time at which these pH jumps occurred depended on the pH of the liquid phase, the concentration of the buffer, the crushing of starting materials, the L/P ratio and the temperature. Good linear correlations were obtained (i) between the time of the pH jumps and the L/P ratio and the temperature and (ii) between the time of the first pH jump and the compressive strength and the final setting time of the cements prepared with different liquid phases. It may be assumed in view of these correlations that the results obtained in dilute solution may be extrapolated to the conditions of cement sample preparation and that the mechanical properties of the cement are directly related to the phenomena that occur at the first pH jump which corresponds to precipitation of dicalcium phosphate dihydrate.     

SAR image filtering based on the heavy-tailed Rayleigh model.

Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori (MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the recently introduced heavy-tailed Rayleigh density function, which was derived based on the assumption that the real and imaginary parts of the received complex signal are best described using the alpha-stable family of distribution. We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the homomorphic MAP filter based on the heavy-tailed Rayleigh prior for the RCS is among the best for speckle removal.     

Arachidonic acid autoxidation in an aqueous media effect of α-tocopherol,cysteine and nucleic acids

The autoxidation of arachidonic acid dispersed in aqueous media was evaluated simultaneously with and without different agents, e.g., α-tocopherol at different concentrations, cysteine, DNA and RNA. The autoxidation rate of arachidonic acid was evaluated by quantitative gas liquid chromatography (GLC) determination of the unoxidized acid and by spectrophotometric measurement of conjugated dienes. α-Tocopherol exhibited a prooxidant activity at concentrations of 1.25 × 10⁻⁴ M and 1.25 × 10⁻⁵ M and a weak antioxidant activity at a concentration of 1.25 × 10⁻⁶ M. Cysteine showed antioxidant activity and greatly reduced the prooxidant activity of α-tocopherol. DNA and RNA had no effect in either case. α-Tocopherol oxidation was followed by high pressure liquid chromatography (HPLC). The prooxidant effect was accompanied by a rapid oxidation of α-tocopherol, except in the presence of cysteine, which prevented the oxidation of α-tocopherol.     

Hyperparameter estimation for satellite image restoration using a MCMC maximum-likelihood method

The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ? function, involving two hyperparameters. Our goal is to estimate the optimal parameters in order to automatically reconstruct images. We propose to use the maximum-likelihood estimator (MLE), applied to the observed image. We need sampling from prior and posterior distributions. Since the convolution prevents use of standard samplers, we have developed a modified Geman-Yang algorithm, using an auxiliary variable and a cosine transform. We present a Markov chain Monte Carlo maximum-likelihood (MCMCML) technique which is able to simultaneously achieve the estimation and the reconstruction.