Vladimir P. Melnik

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Thesis for the degree of Doctor of Technology to be presented with due permission for public examination and criticism in Auditorium HB116, Hermitec at Tampere University of Technology, on the 31st of March 2000, at 12 o'clock noon. Abstract In this thesis, nonlinear locally adaptive techniques of noise removal and restoration are considered for image(More)
We propose a procedure for stack filter design that takes into consideration the filter's sample selection probabilities. A statistical optimization of stack filters can result in a class of stack filters, all of which are statistically equivalent. Such a situation arises in cases of nonsymmetric noise distributions or in the presence of constraints. Among(More)
—A nonlinear multiscale pyramidal transform based on nonoverlapping block decompositions using the median operation and a polynomial approximation is considered. It is shown that this structure can be useful for denoising of one– and two-dimensional (1-D and 2-D) signals. Various denoising techniques are analyzed , including methods based on spatially(More)
The characteristics of impulse bursts in remote sensing images are analyzed and a model for this noise is proposed. The model also takes into consideration other noise types, for example, the multiplicative noise present in radar images. As a case study, soft morphological filters utilizing a training-based optimization scheme are used for the noise(More)
The ways to improve the computational efficiency of the Frost filter and make it robust in respect to spikes are considered. A hard-switching adaptive procedure is proposed and the aspects of proper selection of linear filter parameters and threshold values are discussed. Then the idea of subsequent application of FIR-median hybrid filter is put forward.(More)
The images formed by coherent imaging systems are characterized by presence of multiplicative noise with non-symmetrical p.d.f.s. The examples are the Rayleigh and one-side (negative) exponential distributions. For these cases the optimal L-filters are derived for different coefficient censoring by minimizing MSE of residual fluctuations. Some sub-optimal(More)