No description available.

Kalman filter addresses an estimation problem defined by two models: the signal model and the observation model. In this thesis, the signal model is obtained from a ratio of the defected and clean pictures in frequency domain. The observation model is built for an additive measurement noise from electronic sampling. The statistics of the generating noise for the signal model is important in Kalman filtering. The focus of this thesis is to derive the variance of the generating noise in the middle band for the signal model. By this derived variance, the Kalman filter is thus possible to be applied to estimate the optical transfer function for a defected imaging system in the future.

This research was done to study the effect of sea severity on the vertical ship responses like heave and pitch. Model testing of a 175m moored container ship with zero heading speed was done for different sea states varying from very rough to very high seas. Transfer functions were extracted using Volterra model which constitutes both linear and quadratic part. The experimental linear transfer functions were calculated using Volterra linear model and were compared with linear transfer function from the hydrodynamic theory. Experimental second order transfer functions were also extracted using Volterra quadratic model and their behavior was studied for different sea states. After the extraction of linear and second order transfer functions total responses were reconstructed and compared with the measured responses. This also helped to investigate the contribution of second order part to the total vertical ship responses. In the last stage of the research a new semi- empirical method was developed called as ‘UNIOM’ for the prediction of the responses. Laboratory input waves and theoretical LTFs were used for the simulation of ship response and these were compared with measured responses.

A technique for decomposing the Optical Transfer Function (OTF) into a novel set of basis functions has been developed. The decomposition provides insight into the performance of optical systems containing both wavefront error and apodization, as well as the interactions between the various components of the pupil function. Previously, this technique has been applied to systems with circular pupils with both uniform illumination and Gaussian apodization. Here, systems with annular pupils are explored. In cases of annular pupil with simple defocus, analytic expressions for the OTF decomposition coefficients can be calculated. The annular case is not only applicable to optical systems with central obscurations, but the technique can be extended to systems with multiple ring structures. The ring structures can have constant area as is often found in zone plates and diffractive lenses or the rings can have arbitrary areas. Analytic expressions for the OTF decomposition coefficients again can be determined for ring structures with constant and quadratic phase variations. The OTF decomposition provides a general tool to analyze and compare a diverse set of optical systems.

The lenses are important elements in optical imaging systems. However, lenses are liable to defects such as dusts and thus deteriorate their imaging quality. These kinds of imaging systems are investigated in this thesis .The polluted lens can be verified equivalent to a polluted random screen set against a clean lens .In our model ,the defects on random screen are assumed poisson-distribution ,overlapped and the transmittance effect of each defect is multiplicative .The autocorrelation function of screen is obtained by defects' density ,radius ,and transmittance. The evaluation of the optical transfer function for this imaging system can be achieved by the autocorrelation of the above random screen. This thesis includes computer simulation, experiments and comparison with other model and restoration method. The experiments are set up by the instruments including the video camera , capture card ,and personal computer. We may estimate the key parameters of our theoretical autocorrelation function by the real optical transfer function obtained from experiment. Accordingly, two methods are applied to image restoration in this thesis. One is to use the theoretical autocorrelation, the other is to use a second-order statistics of optical transfer function. The computation of second-order statistics involves a fourfold integration .By the help of changing variables and geometric analysis, we simplify the fourfold integration to double integration. Both of our methods are better for image restoration in RMS value than the method proposed by Tamas Daboczi

No description available.

We derive the expression for the three-dimensional incoherent optical transfer function when third-order spherical aberration is present. The normalized version of the transfer function is numerically calculated for various amounts of spherical aberration. We find the effects of the aberration to be highly dependent on the spatial frequency in the longitudinal direction. We also calculate a structure content parameter, as a quality criterion, from the normalized transfer function. Remarkably, the structure content parameter dependence on spherical aberration is well-fit by a simple Cauchy curve for aberrations out to two waves at the margin.

A fast catchment response usually leads to a shorter lag time, and under these conditions the forecast lead time obtained from a rainfall-runoff model or correlation between upstream and downstream flows may be infeasible for flood warning purposes. Additional lead time can be obtained from short-term quantitative rainfall forecasts that extend the flood warning time and increase the economic viability of a flood forecasting system. For this purpose algorithms which forecasts the quantitative rainfall amounts up to six hours ahead have been developed, based on lumped and distributed approaches. The lumped forecasting algorithm includes the essential features of storm dynamics such as rainband and raincell movements which are represented within the framework of a linear transfer function model. The dynamics of a storm are readily captured by radar data. A space-time rainfall model is used to generate synthetic radar data with known features, e.g. rainband and raincell velocities. This enables the algorithm to be assessed under ideal conditions, as errors are present in observed radar data. The transfer function algorithm can be summarised as follows. The dynamics of the rainbands and raincells are incorporated as inputs into the transfer function model. The algorithm employs simple spatial cross-correlation techniques to estimate the rainband and raincell velocities. The translated rainbands and raincells then form the auxiliary inputs to the transfer function. An optimal predictor based on minimum square error is then derived from the transfer function model, and its parameters are estimated from the auxiliary inputs and observed radar data in real-time using a recursive least squares algorithm. While the transfer-function algorithm forecasts areal rainfalls, a distributed approach which performs rainfall forecasting at a fine spatial resolution (referred to as the advection equation algorithm) is also evaluated in this thesis. The algorithm expresses the space-time rainfall on a Cartesian coordinate system via a partial differential advection equation. A simple explicit finite difference solution scheme is applied to the equation. A comparison of model parameter estimates is undertaken using a square root information filter data processing algorithm, and single-input single-output and multiple-input multiple-output least squares algorithms.

QC 351 A7 no. 53 / The optical performance of three stereomicroscopes commonly used for photo - interpretation is described in terms of magnification, field of view, and square wave response (SqWR). For a given field size, the SqWR can be used to compare the amount of information in the image of each microscope. The SqWR was determined by scanning a square wave test target at four field positions for each of four field sizes (corresponding to magnifications of 6, 12, 25, and 50X). The measured SqWR was used to evaluate the relative ability of each microscope to perform two typical photointerpretation tasks: (1) detailed viewing of a target, and (2) scanning or searching for a target. For these tasks the Wild M -5 stereomicroscope was found to be somewhat better than the Bausch and Lomb 240 stereomicroscope, and both were found to be superior to the Olympus SZ III stereomicroscope. The SqWR curves are included and can be used to compare the stereo - microscopes for various photointerpretation tasks.

This research utilizes the imbibition experiments and X-ray tomography results for modeling fluid flow in naturally fractured reservoirs. Conventional dual porosity simulation requires large number of runs to quantify transfer function parameters for history matching purposes. In this study empirical transfer functions (ETF) are derived from imbibition experiments and this allows reduction in the uncertainness in modeling of transfer of fluids from the matrix to the fracture. The application of the ETF approach is applied in two phases. In the first phase, imbibition experiments are numerically solved using the diffusivity equation with different boundary conditions. Usually only the oil recovery in imbibition experiments is matched. But with the advent of X-ray CT, the spatial variation of the saturation can also be computed. The matching of this variation can lead to accurate reservoir characterization. In the second phase, the imbibition derived empirical transfer functions are used in developing a dual porosity reservoir simulator. The results from this study are compared with published results. The study reveals the impact of uncertainty in the transfer function parameters on the flow performance and reduces the computations to obtain transfer function required for dual porosity simulation.