Performance model of depth from defocus with an unconventional camera.

In this paper, we present a generic performance model able to evaluate the accuracy of depth estimation using depth from defocus (DFD). This model only requires the sensor point spread function at a given depth to evaluate the theoretical accuracy of depth estimation. Hence, it can be used for any (un)conventional system, using either one or several images. This model is validated experimentally on two unconventional DFD cameras, using either a coded aperture or a lens with chromatic aberration. Then, we use the proposed model for the end-to-end design of a 3D camera using an unconventional lens with chromatic aberration, for the specific use-case of small unmanned aerial vehicle navigation.

In-vitro validation of 4D flow MRI measurements with an experimental pulsatile flow model.

PURPOSE: The purpose of this study was to assess the precision of four-dimensional (4D) phase-contrast magnetic resonance imaging (PCMRI) to measure mean flow and peak velocity (Vmax) in a pulsatile flow phantom and to test its sensitivity to spatial resolution and Venc. MATERIAL AND METHODS: The pulsatile flow phantom consisted of a straight tube connected to the systemic circulation of an experimental mock circulatory system. Four-dimensional-PCMR images were acquired using different spatial resolutions (minimum pixel size: 1.5×1.5×1.5mm3) and velocity encoding sensitivities (up to three times Vmax). Mean flow and Vmax calculated from 4D-PCMRI were compared respectively to the reference phantom flow parameters and to Vmax obtained from two-dimensional (2D)-PCMRI. RESULTS: 4D-PCI measured mean flow with a precision of -0.04% to+5.46%, but slightly underestimated Vmax when compared to 2D-PCMRI (differences ranging from -1.71% to -3.85%). 4D PCMRI mean flow measurement was influenced by spatial resolution (P<0.001) with better results obtained with smaller voxel size. There was no effect of Venc on mean flow measurement. Regarding Vmax, neither spatial resolution nor Venc did influence the precision of the measurement. CONCLUSION: Using an experimental pulsatile flow model 4D-PCMRI is accurate to measure mean flow and Vmax with better results obtained with higher spatial resolution. We also show that Venc up to 3 times higher than Vmax may be used with no effect on these measurements.

Modified silver nanowire transparent electrodes with exceptional stability against oxidation.

We report an easy method to prepare thin, flexible and transparent electrodes that show enhanced inertness toward oxidation using modified silver nanowires (Ag NWs). Stabilization is achieved through the adsorption of triphenylphosphine (PPh3) onto the Ag NW hybrid dispersions prior to their 2D organization as transparent electrodes on polyethylene terephtalate (PET) films. After 110 days in air (20 °C) under atmospheric conditions, the transmittance of the PET/Ag NW/PPh3 based films is nearly unchanged, while the transmittance of the PET/Ag NW-based films decreases by about 5%. The sheet resistance increases for both materials as time elapses, but the rate of increase is more than four times slower for films stabilized by PPh3. The improved transmittance and conductivity results in a significantly enhanced stability for the figure of merit σ dc/σ op. This phenomenon is highlighted in highly oxidative nitric acid vapor. The tested stabilized films in such conditions exhibit a decrease to σ dc/σ op of only 38% after 75 min, whereas conventional materials exhibit a relative loss of 71%. In addition, by contrast to other classes of stabilizers, such as polymer or graphene-based encapsulants, PPh3 does not alter the transparency or conductivity of the modified films. While the present films are made by membrane filtration, the stabilization method could be implemented directly in other liquid processes, including industrially scalable ones.

Convex half-quadratic criteria and interacting auxiliary variables for image restoration.

This paper deals with convex half-quadratic criteria and associated minimization algorithms for the purpose of image restoration. It brings a number of original elements within a unified mathematical presentation based on convex duality. Firstly, the Geman and Yang's and Geman and Reynolds's constructions are revisited, with a view to establishing the convexity properties of the resulting half-quadratic augmented criteria, when the original nonquadratic criterion is already convex. Secondly, a family of convex Gibbsian energies that incorporate interacting auxiliary variables is revealed as a potentially fruitful extension of the Geman and Reynolds's construction.

Inversion of large-support ill-posed linear operators using a piecewise Gaussian MRF.

We propose a method for the reconstruction of signals and images observed partially through a linear operator with a large support (e.g., a Fourier transform on a sparse set). This inverse problem is ill-posed and we resolve it by incorporating the prior information that the reconstructed objects are composed of smooth regions separated by sharp transitions. This feature is modeled by a piecewise Gaussian (PG) Markov random field (MRF), known also as the weak-string in one dimension and the weak-membrane in two dimensions. The reconstruction is defined as the maximum a posteriori estimate. The prerequisite for the use of such a prior is the success of the optimization stage. The posterior energy corresponding to a PG MRF is generally multimodal and its minimization is particularly problematic. In this context, general forms of simulated annealing rapidly become intractable when the observation operator extends over a large support. In this paper, global optimization is dealt with by extending the graduated nonconvexity (GNC) algorithm to ill-posed linear inverse problems. GNC has been pioneered by Blake and Zisserman in the field of image segmentation. The resulting algorithm is mathematically suboptimal but it is seen to be very efficient in practice. We show that the original GNC does not correctly apply to ill-posed problems. Our extension is based on a proper theoretical analysis, which provides further insight into the GNC. The performance of the proposed algorithm is corroborated by a synthetic example in the area of diffraction tomography.