Systematic approach to nonlinear filtering associated with aggregation operators. Part 2. Frechet MIMO-filters

Median filtering has been widely used in scalar-valued image processing as an edge preserving operation. The basic idea is that the pixel value is replaced by the median of the pixels contained in a window around it. In this work, this idea is extended onto vector-valued images. It is based on the fact that the median is also the value that minimizes the sum of distances between all grey-level pixels in the window. The Frechet median of a discrete set of vector-valued pixels in a metric space with a metric is the point minimizing the sum of metric distances to the all sample pixels. In this paper, we extend the notion of the Frechet median to the general Frechet median, which minimizes the Frechet cost function (FCF) in the form of aggregation function of metric distances, instead of the ordinary sum. Moreover, we propose use an aggregation distance instead of classical metric distance. We use generalized Frechet median for constructing new nonlinear Frechet MIMO-filters for multispectral image processing. (C) 2017 The Authors. Published by Elsevier Ltd.This work was supported by grants the RFBR No 17-07-00886, No 17-29-03369 and by Ural State Forest University Engineering's Center of Excellence in "Quantum and Classical Information Technologies for Remote Sensing Systems"

Systematic approach to nonlinear filtering associated with aggregation operators. Part 1. SISO-filters

There are various methods to help restore an image from noisy distortions. Each technique has its advantages and disadvantages. Selecting the appropriate method plays a major role in getting the desired image. Noise removal or noise reduction can be done on an image by linear or nonlinear filtering. The more popular linear technique is based on average (on mean) linear operators. Denoising via linear filters normally does not perform satisfactorily since both noise and edges contain high frequencies. Therefore, any practical denoising model has to be nonlinear. In this work, we introduce and analyze a new class of nonlinear SISO-filters that have their roots in aggregation operator theory. We show that a large body of non-linear filters proposed to date constitute a proper subset of aggregation filters. (C) 2017 The Authors. Published by Elsevier Ltd.This work was supported by grants the RFBR No. 17-07-00886 and by Ural State Forest Engineering's Center of Excellence in "Quantum and Classical Information Technologies for Remote Sensing Systems"

Linear codes invariant with respect to generalized shift operators

The purpose of this paper is to introduce new linear codes with generalized symmetry. We extend cyclic and group codes in the following way. We introduce codes, invariant with respect to a family of generalized shift operators (GSO). In particle case when this family is a group (cyclic or Abelian), these codes are ordinary cyclic and group codes. They are invariant with respect to this group. We deal with GSO-invariant codes with fast code and encode procedures based on fast generalized Fouriertransforms. The hope is that these more general structures will lead to larger classes of useful codes “good” properties.This work was supported by grants the RFBR № 17-07-00886and by Ural State Forest Engineering’s Center of Excellence in”Quantum and Classical Information Technologies for Remote Sensing Systems”

Cryptosystems based on RS and BCH codes over finite noncommutative algebras

The purpose of this paper is to introduce new cryptosystems based on linear ReedSolomon (RC) and Bose-Chaudhuri-Hocquenghem (BCH) codes over finite Cayley-Dickson and finite Clifford algebras with fast code and encode procedures based on fast FourierClifford-Galois and Fourier- Cayley-Dickson-Galois transforms.This work was supported by grants the RFBR № 17-07-00886 and by Ural State Forest Engineering’s Center of Excellence in ”Quantum and Classical Information Technologies for Remote Sensing Systems”

Systematic approach to nonlinear filtering associated with aggregation operators. Part 2. Fréchet MIMO-filters

Median filtering has been widely used in scalar-valued image processing as an edge preserving operation. The basic idea is that the pixel value is replaced by the median of the pixels contained in a window around it. In this work, this idea is extended onto vector-valued images. It is based on the fact that the median is also the value that minimizes the sum of distances between all grey-level pixels in the window. The Fréchet median of a discrete set of vector-valued pixels in a metric space with a metric is the point minimizing the sum of metric distances to the all sample pixels. In this paper, we extend the notion of the Fréchet median to the general Fréchet median, which minimizes the Fréchet cost function (FCF) in the form of aggregation function of metric distances, instead of the ordinary sum. Moreover, we propose use an aggregation distance instead of classical metric distance. We use generalized Fréchet median for constructing new nonlinear Fréchet MIMOfilters for multispectral image processing.This work was supported by grants the RFBR No. 17-07-00886 and by Ural State Forest Engineering’s Center of Excellence in ”Quantum and Classical Information Technologies for Remote Sensing Systems”

Systematic approach to nonlinear filtering associated with aggregation operators. Part 1. SISO-filters

There are various methods to help restore an image from noisy distortions. Each technique has its advantages and disadvantages. Selecting the appropriate method plays a major role in getting the desired image. Noise removal or noise reduction can be done on an image by linear or nonlinear filtering. The more popular linear technique is based on average (on mean) linear operators. Denoising via linear filters normally does not perform satisfactorily since both noise and edges contain high frequencies. Therefore, any practical denoising model has to be nonlinear. In this work, we introduce and analyze a new class of nonlinear SISO-filters that have their roots in aggregation operator theory. We show that a large body of non-linear filters proposed to date constitute a proper subset of aggregation filters.This work was supported by grants the RFBR No. 17-07-00886 and by Ural State Forest Engineering’s Center of Excellence in ”Quantum and Classical Information Technologies for Remote Sensing Systems”

Multiparameter Golay m-complementary sequences and transforms

In this paper, we develop the family of Golay-Rudin-Shapiro (GRS) m-complementary sequences.It based on a new generalized iteration generating construction with n unitary (m х m) -transforms U1m, U2m , …,UnmThis work was supported by grants the RFBR № 17-07-00886 and by Ural State Forest Engineering’s Center of Excellence in ”Quantum and Classical Information Technologies for Remote Sensing Systems”