Victor Filippovich Kravchenko

A new class of WA-systems of Kravchenko-Rvachev functions

In this paper, we suggest and substantiate constructions of a new class of WA-systems of Kravchenko‐ Rvachev functions [1, 2] based on atomic functions (AFs) and using the ideas and results of [1‐7]. In the first part, we describe an algorithm for constructing WA-systems of functions, and in the second part, we perform a computational study of a new family of complex wavelets based on AFs and possessing a number of useful properties. These wavelets and their Fourier images are determined by analytical relations.

Development of the theory, methods and algorithms of optimal space-time ultrawideband signal processing for radio-thermal radiation

A new concept for solving statistical synthesis problems of radiometric devices and systems (RDS) is developed. The reasonability of using ultra-wideband (UWB) RDSs is substantiated. The basic data of mathematical apparatus of V-transforms employed when processing space-time UWB fields and their statistical characteristics is given. A wide class of UWB RDS statistical synthesis problems (compensation, zero-type, modified modulation type, modulation compensation type, multi-antenna systems including cross-correlation-compensation systems and aperture synthesis systems) of stationary and scanning types are solved. The appropriateness of using the Kravchenko weighting functions for refinement of primary radiometric images in radiometric scanning devices is substantiated.

Review of modern algorithms for high resolution imaging with passive radar

A review of modern optimal and quasi-optimal algorithms for radiometric signal processing, which provide images with a high spatial resolution is given. It is shown that the high resolution is achieved with ultra-wideband or multi-band time or space-time signal processing. Analytical expressions for the limiting error of image estimation, ambiguity functions and potential fluctuation sensitivity of systems designed according to the algorithms are derived.

Study of the Structure of Solutions to Nonlinear Wave Equations Based on Continuous Wavelet Analysis

Nonlinear waves and oscillations occupy a special place in modern physics and radio physics [1‐7]. However, physical phenomena associated with nonlinear processes have not been thoroughly investigated thus far [7]. Mathematical methods based on wavelet analysis [8‐14] can be promising as applied to the detection of new features of nonlinear processes, waves, and oscillations. In this paper, a new approach based on the continuous wavelet transform is proposed to study the structure of solutions to standard nonlinear equations and the results are compared with those based on the window Fourier transform.

2D to 3D Conversion Based on Disparity Map Estimation

Different hardware implementations of designed automatic 2D to 3D video color conversion employing 2D video and sequence are presented. The analyzed frameworks include together processing of neighboring frames using the following blocks: CIELa*b* color space conversion, wavelet transform (WT) with edge detection using HF wavelet sub-bands (HF, LH and HH) or pyramidal scheme, color segmentation via k-means on a*b* color plane, up-sampling in wavelet case, disparity map (DM) estimation, adaptive post-filtering, and finally, the anaglyph 3D scene generation. The SSIM and QBP criteria are applied in order to compare the performance of the proposed frameworks against other 3D computation techniques. The designed techniques has been implemented on DSP TMS320DM648, Matlab’s Simulink module over a PC with Windows 7, and using graphic card (NVIDIA Quadro K2000) demonstrating that the proposed approach can be applied in real-time processing mode.

Efficient 2D to 3D video conversion implemented on DSP

An efficient algorithm to generate three-dimensional (3D) video sequences is presented in this work. The algorithm is based on a disparity map computation and an anaglyph synthesis. The disparity map was first estimated by employing the wavelet atomic functions technique at several decomposition levels in processing a 2D video sequence. Then, we used an anaglyph synthesis to apply the disparity map in a 3D video sequence reconstruction. Compared with the other disparity map computation techniques such as optical flow, stereo matching, wavelets, etc., the proposed approach produces a better performance according to the commonly used metrics (structural similarity and quantity of bad pixels). The hardware implementation for the proposed algorithm and the other techniques are also presented to justify the possibility of real-time visualization for 3D color video sequences.

The theory of fractal antenna arrays

Foundations of measure theory, the Hausdorff-Besicovitch measure, fractal nowhere differentiable Boltzano, Weierstrass, Cantor, Riemann, Darboux, Van-der-Waerden, Koch, Sierpinski, Besicovitch, and Weierstrass-Mandelbrot functions, and also some atomic functions possessing fractal properties are considered. For the first time, the atomic-fractal functions are constructed. The theory proposed and justified is illustrated on problems of synthesis of radiating structures by means of modeling the corresponding physical processes.

New constructions of digital filters synthesis on base of generalized Kravchenko-Kotelnikov sampling theorem

In this report the new constructions of digital filters are proposed. They are based on the generalized Kravchenko-Kotelnikov sampling theorem. Efficiency of the proposed low- and high- frequency filters is investigated for an example of digital processing of signals.

Integrated nonparametric estimations of probability density of stochastic processes by atomic functions

Integral non-parametric estimations of the probability density and its derivatives [5-8] found on the basis of atomic functions (AF) [1-4] and of results of works [5-7] are presented. This approach enables us to obtain smoother estimations of the probability density, which improves the efficiency of solving the problems of image classification and recognition. The mathematical apparatus of the integral nonparametric statistics enables us to estimate more precisely the sequence characteristics without a priori parametric information.

Video Denoising by Fuzzy Directional Filter Using the DSP EVM DM642

We present a new 3D Fuzzy Directional (3D-FD) algorithm for the denoising of video colour sequences corrupted by impulsive noise. The proposed approach consists of the estimations of movement levels, noise in the neighborhood video frames, permitting to preserve the edges, fine details and chromaticity characteristics in video sequences. Experimental results show that the noise in these sequences can be efficiently removed by the proposed 3D-FD filter, and that the method outperforms other state of the art filters of comparable complexity on video sequences. Finally, hardware requirements are evaluated permitting real time implementation on DSP EVM DM642.