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ANALYSIS OF THE CONTROLLABILITY OF SOME DIGITAL FILTERS WITH A FINITE IMPULSE RESPONSE
D. A. Guzhva , К.О. Sever, А. А. Morozov2021-08-11Abstract ▼This overview article covers finite impulse response filters and filter banks. The use of these filters
for hearing aids is considered. Ways to compensate for hearing loss and ways to increase loudness
using broadband amplification are considered. A schematic diagram of a method for digital
signal processing using a bank of filters, as well as a technique for synthesizing interpolation filters
with low computational complexity, is presented. Also, the application of the MATLAB system for the
synthesis of narrow-band non-recursive FIR filters, their design procedure, methodology and examples
are considered. Finite Impulse Response (FIR) filters and filter banks have specific properties
that guarantee stability. Therefore, they are popular in many applications such as communication
systems, audio signal processing, biomedical instruments, and so on. Unfortunately, due to the longer
wavelength, the cost of implementing an FIR filter is usually not higher than an infinite impulse response
(IIR) filter that meets the same requirements. It is well known that the length of an FIR filter is
inversely proportional to its transition bandwidth. Therefore, the disadvantage becomes acute when a
given filter has a narrow transition band. The main goal is to consider computationally efficient
methods for designing FIR filters and filter banks. The masking method (FRM) results in significant
savings in the number of multipliers. Next, a 16-band, low group delay, non-equal-spacing digital
FIR filter bank is considered. Overall latency is significantly reduced as a result of a new filter structure
that reduces the interpolation factor for prototype filters. Masking filter may be an interpolated
finite impulse response (IFIR) filter that helps reduce complexity. -
COMPARATIVE ANALYSIS OF TWO FILTERING METHODS TO ELIMINATE NOISE IN AN IMAGE OF DIFFERENT DEGREES OF NOISE
K.O. Sever, I.I. Turulin, D.A. Guzhva2021-08-11Abstract ▼In modern photography and video technology, any image in the process of its creation is
distorted by various types of noise. There are various types of noise, but in practice, impulsive and
Gaussian noise models are the most common. Attenuation of the effect of noise is achieved by filtering.
At the moment, there is no universal filter that suppresses noise data at various intens ities
of distortion. Therefore, an important aspect is to determine the field of application of each
type of filter when suppressing noise in the image and creating a filter, consisting of a combination
of different filtering methods for optimal image cleaning. The article presents a comparative
analysis of median filtering and Wiener filtering to eliminate impulse and Gaussian noise in
the image with different degrees of noise. For modeling, we used one image, separately distorted
by impulse and separately by Gaussian noise with pixel distortion probabilities from 1% to
99% inclusive. Filtration was performed with windows equal to 3x3 and 5x5. As a result, we
obtained numerical estimates of the image filtering quality based on the peak signal-to-noise
ratio (PSNR). On the basis of the data obtained, the application of the investigated filters, their
modifications, advantages and disadvantages were analyzed, as well as recommendations for
their use were given. As a result of a comparative analysis of the studied types of filtering for
noisy images, it was found that the median filter with a 3x3 window copes better with image
cleaning from low-intensity impulse noise and with a 5x5 window - with image cleaning with an
average noise intensity. Also, the median filter does a better job of filtering out Waussian noise
at its medium and high rms deviations. The Wiener filter with 3x3 and 5x5 windows better fi lters
Gaussian noise at small values of its root-mean-square deviation. Also, the Wiener filter
copes better with impulse noise with relatively high noise power. -
IMPLEMENTATION OF AN EFFICIENT SEPARABLE VECTOR DIGITAL FILTER ON FPGA
К.О. Sever, К.N. Alekseev, I.I. Turulin2024-08-12Abstract ▼In modern video surveillance systems, in which the use of computer vision technology is widespread,
the most important information in the image is data on the contours of objects and the highlighting of small
details. The systems are subject to stringent requirements, such as: high speed of processing information
from a large number of cameras simultaneously, operation in conditions of poor lighting of the object and
under the influence of external noise (electromagnetic fields, short interference from high-voltage transmission
lines). Therefore, improving image processing methods using parallel computing devices and building a
multi-threaded system is an urgent task. In this work, a 3x3 anisotropic high-pass filter is designed and simulated
for image processing on an FPGA. An algorithm for its construction in the form of a separable vector
representation is described. A detailed description is given of the development of an effective separable twodimensional
digital filter for sharpening and highlighting the boundaries of objects in RGB images. The filter
is based on the synthesis of the proposed 3x3 anisotropic high-pass filter and the Sobel gradient filter.
The corresponding block diagram of the filter has been designed. Based on the results of processing the distorted
image, we can conclude that the developed filter has the property of more uniform detailing and high lighting of objects in the image and is less susceptible to Gaussian noise compared to the Sobel gradient filter
and the Laplace high-pass filter. A filter pipeline circuit has been developed on an FPGA for processing one
plane of an RGB image. Due to the use of separable filters, the proposed implementation is almost 2 times
more optimal in terms of the number of addition/subtraction operations performed than the direct implementation
of a 3x3 Sobel gradient filter and a 3x3 anisotropic high-pass filter. -
RECURSPIVE SEPARABLE 2D DIGITAL FILTER FOR INCREASING THE SHARPNESS OF RGB IMAGES
К. О. Sever, D.А. Guzhva, I.I. Turulin2024-01-05Abstract ▼An important role in the perception of image quality is sharpness, that is, the An important
role in the perception of image quality is played by sharpness, that is, the magnitude of the brightness
gradient in areas near the boundaries of objects. This characteristic is responsible for the
clarity and detail of small image elements. Defocusing the camera lens and insufficient illumination
are the main factors that can lead to digital image blurring. To increase the sharpness, various
processing methods are used, such as filtering in the frequency domain, for example, the use of
fast Fourier transform to emphasize the boundaries and textures of the image. The use of this typeof filtering allows you to control the contrast and frequency content of the image, which leads to
an improvement in visual perception. However, this method has a number of significant drawbacks,
such as logarithmic complexity and performing additional calculations associated with
forward and inverse Fourier transforms. Therefore, the preferred method of image sharpening is
the so-called spatial processing, which provides direct filtering of image pixels without additional
transformations, and the reuse of processing results (recursive component) in the filter allows you
to reduce the number of operations, reduce computational complexity. The article describes the
development of an effective recursive separable two-dimensional digital filter to sharpen largedimensional
RGB images. The algorithms of its construction are given, the corresponding block
diagrams are designed. The filter has the property of more uniform detail of image objects, and is
less susceptible to the creation of pulse noise. Also, for the original high-resolution RGB image, a
blur filter is modeled, the matrix of which is filled according to the normal (Gaussian) law.
To assess the filtration quality, the developed filter is compared with the algorithm of classical
two-dimensional convolution with a 5x5 Laplace high-pass filter core. -
8-BAND HETEROGENEOUS BANK OF FIR FILTERS WITH HIGH COMPUTATIONAL EFFICIENCY FOR HEARING AIDS
D.А. Guzhva, К. О. Sever, I.I. Turulin2024-01-05Abstract ▼This article discusses recursive filters with finite impulse response and filter banks. The filter
bank is an array of bandpass filters. The analysis filter block divides the input signal into several
components, with each of the sub-filters carrying one frequency sub-band of the original signal.
On the contrary, the synthesis filter block combines the output data of the sub-bands to restore
the original input signal. In most applications, certain frequencies are more important than others.
Filter blocks can isolate various frequency components in the signal. This way we can put more
effort into processing more important components and less effort into processing less important
components. Subband filters can be combined with step-down or step-up sampling to form a bank
of multi-speed filters. Filter banks are widely used for speech recognition and speech quality improvement.
Currently, filter banks have expanded their application to video and image processing.
In addition, filter blocks are very useful in communication systems, including digital receivers and
transmitters, pre-coding of filter blocks for channel alignment, discrete multi-tone modulation and
blind channel alignment. The use of these filters for hearing aids is considered. An 8-band heterogeneous
bank of recursive filters with finite impulse response (FIR) with high computational efficiency
for hearing aids has been developed. The computational complexity (BC) of a recursive
filter with a finite impulse response (RCIHF) is also compared with the computational complexity
of non-recursive filters with a finite impulse response (NCIHF).








