Conveyorized implementation of ASWM image filter on PLD

The object of research is the adaptive switching weighted median image filter (ASWM) algorithm. This algorithm is one of the most effective in the field of impulse noise suppression. The computational complexity and algorithmic features of this adaptive nonlinear filter make it impossible to impleme...

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Main Authors: Oleg Vasylchenkov, Igor Liberg, Mykhailo Mozhaiev, Dmytro Salnikov
Format: Article
Language:English
Published: PC Technology Center 2021-02-01
Series:Technology Audit and Production Reserves
Subjects:
Online Access:http://journals.uran.ua/tarp/article/view/225257
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spelling doaj-139bbd7c3f5649ccb711af192f825d232021-03-11T15:55:09ZengPC Technology CenterTechnology Audit and Production Reserves2664-99692706-54482021-02-0112(57)61110.15587/2706-5448.2021.225257262731Conveyorized implementation of ASWM image filter on PLDOleg Vasylchenkov0https://orcid.org/0000-0002-0969-2248Igor Liberg1https://orcid.org/0000-0002-2404-5620Mykhailo Mozhaiev2https://orcid.org/0000-0003-1566-9260Dmytro Salnikov3https://orcid.org/0000-0002-0490-4061National Technical University «Kharkiv Polytechnic Institute»National Technical University «Kharkiv Polytechnic Institute»National Scientific Center «Hon. Prof. M. S. Bokarius Forensic Science Institute»National Technical University «Kharkiv Polytechnic Institute»The object of research is the adaptive switching weighted median image filter (ASWM) algorithm. This algorithm is one of the most effective in the field of impulse noise suppression. The computational complexity and algorithmic features of this adaptive nonlinear filter make it impossible to implement a filter that works in real time on modern PLD microcircuits. The most problematic areas of the algorithm are the weight coefficient estimation cycle, which has no limit on the number of iterations and contains a large number of division operations. This does not allow implementing the filter on PLDs with a sufficiently effective method. In the course of the research, the programming model of the filter in Python was used. The performance of the algorithm was assessed using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics. Modeling made it possible to find out empirically the number of iterations of the cycle for estimating the weight coefficients at different levels of noise density and to estimate the effect of artificial limitation of the maximum number of iterations on the filter performance. Regardless of the intensity of the noise impact, the algorithm performs less than 40 iterations of the evaluation cycle. Let’s also simulate the operation of the algorithm with different variants of the division module implementation. The paper considers the main of them and offers the most optimal in terms of the ratio of accuracy/hardware costs for implementation. Thus, a modified algorithm was proposed that does not have these disadvantages. Thanks to modifications of the algorithm, it is possible to implement a pipelined ASWM image filter on modern PLDs. The filter is synthesized for the main families of Intel PLDs. The implementation, which is not inferior in terms of SSIM and PSNR metrics to the original algorithm, requires less than 65,000 FPGA logical cells and allows filtering of monochrome images with FullHD resolution at 48 frames/s at a clock frequency of 100 MHz.http://journals.uran.ua/tarp/article/view/225257adaptive filternonlinear filtermedian filterimpulse noisepeak signal-to-noise ratiostructural similarity index measure
collection DOAJ
language English
format Article
sources DOAJ
author Oleg Vasylchenkov
Igor Liberg
Mykhailo Mozhaiev
Dmytro Salnikov
spellingShingle Oleg Vasylchenkov
Igor Liberg
Mykhailo Mozhaiev
Dmytro Salnikov
Conveyorized implementation of ASWM image filter on PLD
Technology Audit and Production Reserves
adaptive filter
nonlinear filter
median filter
impulse noise
peak signal-to-noise ratio
structural similarity index measure
author_facet Oleg Vasylchenkov
Igor Liberg
Mykhailo Mozhaiev
Dmytro Salnikov
author_sort Oleg Vasylchenkov
title Conveyorized implementation of ASWM image filter on PLD
title_short Conveyorized implementation of ASWM image filter on PLD
title_full Conveyorized implementation of ASWM image filter on PLD
title_fullStr Conveyorized implementation of ASWM image filter on PLD
title_full_unstemmed Conveyorized implementation of ASWM image filter on PLD
title_sort conveyorized implementation of aswm image filter on pld
publisher PC Technology Center
series Technology Audit and Production Reserves
issn 2664-9969
2706-5448
publishDate 2021-02-01
description The object of research is the adaptive switching weighted median image filter (ASWM) algorithm. This algorithm is one of the most effective in the field of impulse noise suppression. The computational complexity and algorithmic features of this adaptive nonlinear filter make it impossible to implement a filter that works in real time on modern PLD microcircuits. The most problematic areas of the algorithm are the weight coefficient estimation cycle, which has no limit on the number of iterations and contains a large number of division operations. This does not allow implementing the filter on PLDs with a sufficiently effective method. In the course of the research, the programming model of the filter in Python was used. The performance of the algorithm was assessed using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics. Modeling made it possible to find out empirically the number of iterations of the cycle for estimating the weight coefficients at different levels of noise density and to estimate the effect of artificial limitation of the maximum number of iterations on the filter performance. Regardless of the intensity of the noise impact, the algorithm performs less than 40 iterations of the evaluation cycle. Let’s also simulate the operation of the algorithm with different variants of the division module implementation. The paper considers the main of them and offers the most optimal in terms of the ratio of accuracy/hardware costs for implementation. Thus, a modified algorithm was proposed that does not have these disadvantages. Thanks to modifications of the algorithm, it is possible to implement a pipelined ASWM image filter on modern PLDs. The filter is synthesized for the main families of Intel PLDs. The implementation, which is not inferior in terms of SSIM and PSNR metrics to the original algorithm, requires less than 65,000 FPGA logical cells and allows filtering of monochrome images with FullHD resolution at 48 frames/s at a clock frequency of 100 MHz.
topic adaptive filter
nonlinear filter
median filter
impulse noise
peak signal-to-noise ratio
structural similarity index measure
url http://journals.uran.ua/tarp/article/view/225257
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