Keith Hopcraft

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Results are presented that demonstrate the effectiveness of using polarization discrimination to improve visibility when imaging in a scattering medium. The study is motivated by the desire to improve visibility depth in turbid environments, such as the sea. Most previous research in this area has concentrated on the active illumination of objects with(More)
A simple image-subtraction technique for further enhancement of the visibility depth in polarized imaging of surfaces immersed in scattering media is proposed and assessed. The technique is based on active illumination with circular or linear polarization states and image detection in the original and the opposite, or orthogonal, states. Contrast(More)
Laser Doppler flowmetry relies upon the use of the first moment of the power spectrum of the photocurrent and numerous methods of providing an estimate of this have been implemented. One, operating in the time domain and using only a few, simple processing steps, is claimed to be both fast and accurate (Draijer et al. in Med Biol Eng Comput(More)
A relationship is established between the autocorrelation function of continuous Gaussian and non-Gaussian stochastic processes and the discrete process that describes their zero or level crossings. Random fractals occur when the distribution for the number of crossings is described by a class of Markov processes whose singlefold statistics are the discrete(More)
Diagnostics applied to a rice-pile cellular automaton reveal different mechanisms producing power-law behaviors of statistical attributes of grains which are germane to self organised critical phenomena. The probability distributions for these quantities can be derived from two distinct random walk models that account for correlated clustered behavior(More)
The stochastic point processes formed by the zero crossings or extremal points of differentiable, stationary Gaussian processes are studied as a function of their autocorrelation function. The properties of these point processes are mapped to the space formed by the parameters appearing in the autocorrelation function, their adopted form being sensitive to(More)
The characterisation of time-series data via their most salient features is extremely important in a range of machine learning task, not least of all with regards to classification and clustering. While there exist many feature extraction techniques suitable for non-intermittent time-series data, these approaches are not always appropriate for intermittent(More)
In manufacturing left-handed media the interfaces will never be perfect; defects and other disturbances to interfaces and material parameters are unavoidable. We report an analytical calculation of electromagnetic wave propagation through a perfect lens with diffuse boundaries. Field localizations are generated in the boundary layers, and the lens' ability(More)
A slab of left-handed material (LHM) with refractive index -1 forms a perfect lens that retains subwavelength information about a source or object. Such lenses are highly susceptible to perturbations affecting their performance. It is shown that illuminating a roughened interface between air and an LHM produces a regime for enhanced focusing of light close(More)
We analyse a number of stochastic processes that give rise to first-order number statistics governed by Laguerre distributions with properties that lie between Poisson and geometric random variables. These distributions have hitherto been used to characterize the photon statistics of a coherent mixture of thermal and laser light. Here, we explore a number(More)