Moshe Fisher

Image resolution limits resulting from mechanical vibrations. Part III:numerical calculation of modulation transfer function

Low-frequency mechanical vibrations are a significant problem in robotics, machine vision, and practical reconnaissance where primary image vibrations involve random process blur radii. They cannot be described by an analytical MTF. A method of numerical calculation of MTF, relevant in principle to any type of image motion, is presented. It is demonstrated here for linear, high, and low vibration frequencies. The method yields the expected closed form solutions for linear and high-frequency motion. The low-vibration-frequency situation involves random process blur radii and MTFs that can only be handled statistically since no closed form solution is possible. This is illustrated here. Comparisons are made to a closed form approximate MTF solution suggested previously for low-frequency motion. Agreement between that analytical approximation and exact MTF calculated numerically is generally good, especially for relatively large and linear motion blur radius situations. For nonlinear short exposure motion, MTF levels off at relatively high nonzero values and never approaches zero. Such situations yield a two-fold benefit: (1) larger spatial frequency bandwidth and (2) higher MTF values at all spatial frequencies since MTF does not approach zero.

Development of a double pellet ThO2-UO2

The influence of the properties and the treatments of UO2 and ThO2 powders on the preparation of a double pellet composed by UO2 inner core and ThO2 outer hollow cylinder was studied. Although a simultaneous pressing-sintering process is preferable due to its relative simplicity and quickness, good (uncracked) double pellets were manufactured only by a two-step separate UO2 and ThO2 pressing and sintering. Different shrinkage kinetics of the two components are responsible for this behaviour.

A quantitative interpretation of the surface segregation in air-exposed intermetallic compounds: a test case UNiAl

The first quantitative interpretation of the surface segregation in an air-exposed intermetallic compound, namely UNiAl, has been proposed. The analysis of the experimental data indicates that the driving force for the segregation is associated with the surface free energy of the pure metal constituents of the intermetallic compound. The slope of the surface abundance vs surface energy curve differs by approximately a factor of 8 from the slope predicted by a Boltsmann-type distribution function. The same slope is also derived by analyzing the segregation properties of Zr, Cr and Mn in ZrCr2 and ZrMn2, previously studied by other investigators.

Segregation behavior of the intermetallic compounds ZrNiAl, YNiAl and UNiAl

Abstract The surface layers of the intermetallics ANiAl (A = Zr, Y, U), exposed to the ambient air, residual gases and oxygen, were investigated by X-ray photoelectron spectroscopy. The surface and the oxidation energies of the metal components were considered as the possible driving forces for the surface decomposition. A “rule of reverse stability” exists for the three isostructural compounds, i.e., the less stable one (UNiAl) exhibits the most significant segregation. An extrapolated degree of segregation of the air-exposed intermetallics yields a good agreement with previously proposed quantitative model.

The leaching-activation process of Urushibara catalysts

Abstract The acid-leaching process resulting in the activation of Urushibara-Ni catalysts was studied by means of X-ray photoelectron spectroscopy (XPS), X-ray diffraction, scanning electron microscopy (SEM) combined with X-ray energy dispersion (EDX), and wet chemical analysis. The leaching-induced activation has been shown to involve the dissolution of a coating surface layer dominated by zinc compounds and the exposure of metallic nickel. Metallic zinc coexisting with the nickel on the activated surface prevents (at low oxidation doses) the oxidation of the inherently active nickel, by gettering the oxidizing molecules. Exposing the active surface to high oxidation doses results in the oxidation of both metallic constituents and the loss of catalytic activity.

Electron binding energies and oxidation behaviour in UNiAl, YNiAl and ZrNiAl

Abstract The electron binding energies of the metal components on the surface layers of ANiAl (A ≡ U, Y, Zr) were examined by X-ray photoelectron spectroscopy (XPS). The samples were initially exposed to air and then a depth profile was performed utilizing argon ions of energy 1 kV. The constituents were in oxidized states before the sputtering procedure and their bulk electron binding energies were significantly different from those of the pure metals. In the usual experimental XPS set-up the binding energies are related to the Fermi level of the sample. To obtain the total electron binding energy (i.e. related to the vacuum level of the sample), a knowledge of the relevant work functions is required. The work function of UNiAl was estimated by operating the Auger electron spectroscopy (AES) pulse counting mode at low electron kinetic energies. The electron binding energies obtained in this way showed an improved correlation with the electronegativity values of the metal components. The metal electron binding energies demonstrate a complete surface oxidation only on UNiAl after exposures of up to 80 langmuirs of O2. The corresponding oxygen to metals (U + Ni + Al) atomic ratio is significantly lower than the ratio expected from the relevant binary oxides. This behaviour may be accounted for by the formation of ternary oxides or if oxygen is absent from the first atomic layer of the oxidized UNiAl. The latter possibility is considered in view of the absence of oxygen from the first atomic layer of oxidized UFe2 surface as reported by Erbudak and Stucki.

Restoration of images degraded by motion

Low frequency sinusoidal motion involves random process blur length. Restoration of blurred images degraded by this type of motion is more complicated than other images blurred by relative motion between the target and the camera. Results are presented from low frequency motion experiments in which all parameters were measured and used to calculate numerically the optical transfer function (OTF) which was used to restore the blurred image with a wiener filter approach. These results are much better than those achieved using linear motion OTF and high frequency motion OTF. This method for calculating numerically OTF and applying it to image restoration of blurred images can be used for any type of vibration or motion.

Numerical calculation of image motion and vibration modulation transfer function

In many high-resolution photographic and photoelectronic imaging systems, resolution is limited by image motion and vibration and, as a result, the high-resolution capability of the sensor may be wasted. In normal reconnaissance and robotics the sensor moves during the exposure. Some of the resulting image motion can be removed by mechanical compensation, but not all of it. The residual motion blurs the image, and usually this blur becomes the limiting factor for many high-quality imaging systems. The ever-increasing altitudes and coverage requirements of modern imaging have put a premium on high resolution. An application of this paper is the recovery of the original image by inverse filtering that depends on the modulation transfer function (MTF) of the real-time relative motion between the object and the imaging system. An original method developed here for numerically calculating MTF for any type of image motion is the basis of the paper.

Numerical calculation of modulation transfer functions for low-frequency mechanical vibrations

Numerical calculations of modulation transfer functions (MTFs) for low-frequency mechanical vibrations are presented. The problem is significant in practical reconnaissance where primary vibrations are at frequencies too low to be described by the usual closed form Bessel function MTF. The low vibration frequency situation involves random process blur radii and MTFs which can only be handled statistically since no closed form solution is possible. This is illustrated here. Comparisons are made to a closed form approximate MTF solution suggested previously. Agreement is generally good, especially for relatively large and linear blur radius situations.