Vladimir P. Melnik

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In this thesis, nonlinear locally adaptive techniques of noise removal and restoration are considered for image processing applications in mixed noise environments. These techniques are designed and tested for radar, ultrasound, and gray-level test images. The image observation models take into account the influence of fluctuating (additive and(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)
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)
Novel adaptive robust filtering algorithms applicable to radar image processing are proposed. They take into consideration the peculiarities of radar images and possess a good combination of properties: effective speckle suppression, impulsive noise removal, edge and detail preservation and low computational complexity. The advantages of these digital(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)