Reduction of Multiplicative Noise in Radar Images

Introduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction...

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Main Authors: A. A. Tuzova, V. A. Pavlov, A. A. Belov
Format: Article
Language:Russian
Published: Saint Petersburg Electrotechnical University "LETI" 2021-09-01
Series:Известия высших учебных заведений России: Радиоэлектроника
Subjects:
Online Access:https://re.eltech.ru/jour/article/view/537
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author A. A. Tuzova
V. A. Pavlov
A. A. Belov
author_facet A. A. Tuzova
V. A. Pavlov
A. A. Belov
author_sort A. A. Tuzova
collection DOAJ
description Introduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. The values of these parameters have to be selected experimentally. In works devoted to speckle noise filtering, the methods used for selecting filter paraments are rarely clarified.Aim. To present a methodology for selecting the parameters of multiplicative speckle noise filters on a radar image that are optimal in terms of the quality of the resulting image.Materials and methods. The article presents a method for determining the optimal parameters of speckle noise reduction filters. This method was applied to the most conventionally used filters. The search for optimal parameters and testing of the filters were carried out using a specially designed image, which contained the objects most frequently found on radar images. The structural similarity index (SSIM) metric was chosen as a metric that assesses the quality of filtration.Results. After determining the optimal (in terms of SSIM) parameters of speckle noise reduction filters, the filters were compared to select the best filters in terms of the quality of radar image processing. In addition, the operation of the filters under study was tested on images containing various types of objects, namely: large objects, small objects and sharp borders. Knowing which filter copes best with smoothing speckle noise in a particular area and what values of the variable parameters this requires, an optimal quality of radar images can be achieved. Filtering not only improves human perception of radar images, but also reduces the influence of speckle noise during their further processing (object detection, segmentation of areas, etc.).Conclusion. The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. The quality of filtration was assessed using an expert method (visually) by comparing images before and after filtration, differential images and one-dimensional image slices. The Frost filter and the anisotropic diffusion filter with optimal parameters showed the best processing quality according to the SSIM metric.
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spelling doaj.art-bb1cafeb388e47ba93fde5a623fafbaf2023-03-13T09:20:24ZrusSaint Petersburg Electrotechnical University "LETI"Известия высших учебных заведений России: Радиоэлектроника1993-89852658-47942021-09-0124461810.32603/1993-8985-2021-24-4-6-18396Reduction of Multiplicative Noise in Radar ImagesA. A. Tuzova0V. A. Pavlov1A. A. Belov2Санкт-Петербургский государственный морской технический университетСанкт-Петербургский политехнический университет Петра ВеликогоСанкт-Петербургский политехнический университет Петра ВеликогоIntroduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. The values of these parameters have to be selected experimentally. In works devoted to speckle noise filtering, the methods used for selecting filter paraments are rarely clarified.Aim. To present a methodology for selecting the parameters of multiplicative speckle noise filters on a radar image that are optimal in terms of the quality of the resulting image.Materials and methods. The article presents a method for determining the optimal parameters of speckle noise reduction filters. This method was applied to the most conventionally used filters. The search for optimal parameters and testing of the filters were carried out using a specially designed image, which contained the objects most frequently found on radar images. The structural similarity index (SSIM) metric was chosen as a metric that assesses the quality of filtration.Results. After determining the optimal (in terms of SSIM) parameters of speckle noise reduction filters, the filters were compared to select the best filters in terms of the quality of radar image processing. In addition, the operation of the filters under study was tested on images containing various types of objects, namely: large objects, small objects and sharp borders. Knowing which filter copes best with smoothing speckle noise in a particular area and what values of the variable parameters this requires, an optimal quality of radar images can be achieved. Filtering not only improves human perception of radar images, but also reduces the influence of speckle noise during their further processing (object detection, segmentation of areas, etc.).Conclusion. The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. The quality of filtration was assessed using an expert method (visually) by comparing images before and after filtration, differential images and one-dimensional image slices. The Frost filter and the anisotropic diffusion filter with optimal parameters showed the best processing quality according to the SSIM metric.https://re.eltech.ru/jour/article/view/537радиолокационное синтезирование апертурырадиолокационное изображениеспекл-шумфильтрация спекл-шумапараметры фильтров
spellingShingle A. A. Tuzova
V. A. Pavlov
A. A. Belov
Reduction of Multiplicative Noise in Radar Images
Известия высших учебных заведений России: Радиоэлектроника
радиолокационное синтезирование апертуры
радиолокационное изображение
спекл-шум
фильтрация спекл-шума
параметры фильтров
title Reduction of Multiplicative Noise in Radar Images
title_full Reduction of Multiplicative Noise in Radar Images
title_fullStr Reduction of Multiplicative Noise in Radar Images
title_full_unstemmed Reduction of Multiplicative Noise in Radar Images
title_short Reduction of Multiplicative Noise in Radar Images
title_sort reduction of multiplicative noise in radar images
topic радиолокационное синтезирование апертуры
радиолокационное изображение
спекл-шум
фильтрация спекл-шума
параметры фильтров
url https://re.eltech.ru/jour/article/view/537
work_keys_str_mv AT aatuzova reductionofmultiplicativenoiseinradarimages
AT vapavlov reductionofmultiplicativenoiseinradarimages
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