Fuzzy-based frost filter for speckle noise reduction of Synthetic Aperture Radar (SAR) image

The Synthetic Aperture Radar (SAR) image is a high-resolution image and is less influenced by weather conditions either day or night compared to the optical image. SAR image, because of its advantages, is becoming more popular than the optical image in the remote sensing area for earth observation study. However, the speckle noise that occurs in the SAR image causes difficulties in image interpretation, and speckle noise reduction process has become necessary before of the usage of SAR image. The ideal speckle filter has the capability of reducing speckle noise without losing the information and preserving its texture. This study proposes the use of speckle noise filter that as nearly possible to meet those criteria. This research has investigated the performance of existing filter, which was Frost, Lee, Kuan, and Median, and had applied it to ALOS-PALSAR images with homogeneous and heterogeneous earth area surfaces in Kuantan, Pahang, Malaysia. Filtered image is measured and evaluated using image quality parameters to show the performance of the filters in reducing speckle noise and preserving the texture. The parameter used for filters evaluation performances are Equivalent Number of Looks (ENL), Speckle Index (SI), Mean, Standard Deviation and Variance. The experiment results showed that Frost filter has better results compared to others and has been selected as the qualified existing filter. The Frost filter was modified by applying the fuzzy approach which was aimed at eliminating speckle noise while maintaining texture. There are four combinations of proposed filter, which are Frost-ATMAV, Frost-ATMED, Frost-TMAV, and Frost-TMED combination. Based on the results of comparison and evaluation of the filters, Frost-TMAV combination has been selected as the best-proposed filter. It had improved the performance of Frost filters for each parameter's measurement; it showed the improvement value of 19.47% for ENL, 8.48% for SI, 2.56% for mean, 6.15% for standard deviation and 2.00% for a variance, applied into homogeneous areas of ALOS-PALSAR images. While when used with heterogeneous areas, it improved 9.54% for ENL, 4.41% for SI, 3.03% for mean, 1.51% for standard deviation and 2.96% for the variance. It has been verified that the Frost-TMAV could be used for ALOS-PALSAR data pre-processing, which means that this filter can produce good-quality images based on parameters used when compared with other filters

Подавление мультипликативного шума на радиолокационных изображениях

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.Введение. Радиолокационное изображение (РЛИ) – это изображение, получаемое зондированием земной поверхности с помощью радиолокационного устройства. РЛИ обладает важной особенностью в виде спекл-шума, который вызывает зернистость фона. Данный шум необходимо фильтровать с целью улучшения качества РЛИ. Фильтры спекл-шума часто имеют в своей структуре один или несколько параметров, которые контролируют уровень сглаживания шума и значения которых приходится подбирать экспериментально. В статьях, посвященных фильтрации спекл-шума, авторы часто не поясняют, как были выбраны значения параметров фильтров.Цель работы. Представление методики для выбора оптимальных в смысле качества получаемого изображения параметров фильтров мультипликативного спекл-шума на РЛИ.Материалы и методы. Рассмотрена разработанная методика поиска оптимальных параметров фильтров спекл-шума применительно к наиболее часто используемым фильтрам. Поиск оптимальных параметров и тестирование работы фильтров проводятся на специально разработанном изображении, содержащем объекты, наиболее часто встречающиеся на РЛИ. Метрикой, оценивающей качество проведенной фильтрации, служил индекс структурного сходства SSIM (Structural Similarity Index Metric).Результаты. После нахождения оптимальных по SSIM параметров рассматриваемых фильтров проведено сравнение работы фильтров с точки зрения обработки РЛИ и найдены наилучшие фильтры для этой задачи. Также работа рассматриваемых фильтров протестирована на изображениях, содержащих различные типы объектов, а именно: большие объекты, мелкие объекты, резкие границы. Зная, какой фильтр наилучшим образом справляется со сглаживанием шума на той или иной области и какие для этого необходимы значения варьируемых параметров, можно использовать полученные результаты для фильтрации радиолокационных изображений. Фильтрация не только улучшает восприятие РЛИ человеком, но и позволяет снизить влияние спекл-шума на дальнейшую автоматизированную обработку РЛИ (детектирование объектов, сегментация областей и др.).Заключение. Предложенный алгоритм позволил найти оптимальные параметры для нескольких фильтров спекл-шума. Качество фильтрации оценивалось экспертным способом (визуально), посредством сравнения изображений до и после фильтрации, разностных изображений и одномерных срезов изображений. Фильтр Фроста и фильтр анизотропной диффузии с оптимальными параметрами показали лучшее качество обработки по SSIM

Standardized Analysis Ready (STAR) data cube for high-resolution Flood mapping using Sentinel-1 data

Floods are one of the most common disasters globally. Flood affects humans in many ways. Therefore, rapid assessment is needed to assess the effect of floods and to take early action to support the vulnerable community in time. Sentinel-1 is one such Earth Observation (EO) mission widely used for mapping the flooding conditions at a 10m scale. However, various preprocessing steps are involved before analyses of the Sentinel-1 data. Researchers sometimes avoid a few necessary corrections since it is time-consuming and complex. Standardization of the Sentinel-1 data is the need of the hour, specifically for supporting researchers to use the Standardized Analysis-Ready (STAR) data cube without experiencing the complexity of the Sentinel-1 data processing. In the present study, we proposed a workflow to use STAR in Google Earth Engine (GEE) environment. The Nigeria Flood of 2022 has been used as a case study for assessing the model performance

МЕТОДИКА ВЫБОРА ФИЛЬТРА ДЛЯ СГЛАЖИВАНИЯ СПЕКЛ-ШУМА РАДАРНЫХ ИЗОБРАЖЕНИЙ С СИНТЕЗИРОВАННОЙ АПЕРТУРОЙ

A method for comparison of different SAR image filtration techniques is presented. It allows selecting the filters with better speckle noise smoothing effect. Unlike the known approaches, the presented method is based on ENL parameter calculation for automatically selected areas.Предлагается методика сравнения результатов фильтрации радарных изображений с синтезированной апертурой разными типами фильтров. С ее помощью можно выбирать фильтры, которые лучше других сглаживают исследуемое изображение. Методика базируется на оценке параметра ENL, который, в отличие от известных подходов, вычисляется для автоматически выбираемых участков изображения

Shoreline Detection Using TerraSAR-X Quad Polarization Mode

In the Netherlands, the coastal zone is a dynamic area because of the geographic position. Economic activities and effects of global warming demand a frequent, accurate and detailed update of the coastline information. For this study, TerraSAR-X quad polari-zation was obtained at 6.6 m azimuth resolution during the Dual Receive Antenna (DRA) campaign. The coastline is detected by decomposing the polarimetric SAR components in three different scattering mechanisms: volume scatter, double bounce scatter, and surface scatter. This composite scattering model allows to classify the image based on these dif-ferent scattering mechanisms. After the decomposition, region growing segmentation is applied to group neighboring pixels with similar values to identify the coastline as the boundary between land and sea. Scheveningen beach has been chosen as case study. The primary methodology is the Freeman and Durden decomposition followed by two clas-sifications (1) Wishart supervised with Maximum Likelihood and without supervised classi-fication and region growing segmentation or (2) with segmentation applied directly to the decomposition results. The output segmentation vector is validated by comparing with nautical charts. After the decomposition and classification of the scatter mechanism, statis-tics showed good signature separability. The region growing segmentation gives good out-puts according to the difference in group pixels related to the land and those related to the sea.En los Países Bajos, la zona costera es una zona dinámica a causa de la posición geográfica. Las actividades económicas y los efectos del calentamiento mundial exigen una actualización frecuente, precisa y detallada de la información de la línea de costa. Para este estudio, se obtuvo la polarización cuadrangular TerraSAR-X a una resolución en acimut de 6,6 m durante la campaña DRA (Antena de Doble Recepción). La línea de costa es detectada mediante la descomposición de los componentes polarimétricos SAR en tres mecanismos diferentes de dispersión: dispersión de volumen, dispersión de doble rebote, y dispersión de superficie. Este modelo de dispersión compuesto permite clasifi-car la imagen basándose en estos mecanismos de dispersión diferentes. Después de la descomposición , la segmentación de crecimiento de regiones se aplica a los píxeles colindantes agrupados con valores similares para identificar la línea de costa como límite entre tierra y mar. Se ha elegido como estudio de caso la playa de Scheveningen. La me-todología principal es la descomposición de Freeman y Durden, seguida de dos clasifica-ciones: (1) la clasificación de Wishart, supervisada por un máximo de probabilidad y la segmentación por enfoque de “región” o (2) la segmentación aplicada directamente a los resultados de la descomposición. El vector de salida de la segmentación se valida me-diante la comparación de las cartas náuticas. Tras la descomposición y la clasificación del mecanismo de dispersión, las estadísticas mostraron una buena separabilidad de distinti-vos. La segmentación por enfoque de “región” proporciona buenos resultados según la diferencia observada entre los grupos de píxeles relativos a la tierra y los relativos al mar.Aux Pays-Bas, la bande côtière est une zone dynamique de par sa position géographi-que. Les activités économiques et les effets du réchauffement climatique requièrent une mise à jour fréquente, précise et détaillée des informations relatives au trait de côte. Dans le cadre de cette étude, des images en polarisation quadruple de TerraSAR-X ont été obtenues avec une résolution en azimut de 6,6 m pendant la campagne « Dual Receive Antenna » (DRA – antenne en mode de réception double). Le trait de côte est détecté par la décomposition des composantes SAR polarimétriques selon trois mécanismes de diffu-sion : diffusion volumique, diffusion double-bonds, et diffusion surfacique. Ce modèle de diffusion composite permet la classification de l’image à partir de ces différents mécanis-mes de diffusion. Après la décomposition, la segmentation par approche « région » est appliquée à un groupe de pixels voisins ayant des valeurs similaires pour identifier le trait de côte en tant que frontière entre la terre et la mer. La plage de Scheveningen a été choisie pour une étude de cas. La principale méthode est la décomposition de Freeman et Durden suivie de deux classifications (1) la classification de Wishart, supervisée par maximum de vraisemblance et sans supervision, et la segmentation par approche « région » ou (2) l’application directe de la segmentation aux résultats de la décomposi-tion. Le vecteur de segmentation en sortie est validé par comparaison avec les cartes marines. Après décomposition et classification du mécanisme de diffusion, les statistiques ont montré une séparabilité des signatures satisfaisante. La segmentation par approche « région » donne de bons résultats d’après la différence observée entre les groupes de pixels relatifs à la terre et ceux relatifs à la mer

Optimum graph cuts for pruning binary partition trees of polarimetric SAR images

This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph cut called pruning to extract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and analyzed in the context of PolSAR images for segmentation. Through the objective evaluation of the resulting partitions by means of precision-and-recall-for-boundaries curves, the best pruning technique is identified, and the influence of the tree construction on the performances is assessed.Peer ReviewedPostprint (author's final draft

Investigating rapid deforestation and carbon dioxide release in Bangladesh using geospatial information from remote sensing data

Rapid deforestation over the last few years due to the massive influx of refugees from neighboring Myanmar has been reported and is seen as a precursor to environmental disaster, raising the need for more effective monitoring of forest areas. The availability of data from several space-borne synthetic aperture radar (SAR) missions allow enhanced monitoring of forest areas. The objective of this study was to map deforestation in two selected areas located in northeast and southeast Bangladesh using Sentinel-1 imageries and determine the applicability of SAR in forest monitoring in Bangladesh. Towards these purpose satellite imageries from 2017 and 2018 collected by Sentinel-1A and Sentinel-1 Band SAR data in dual-polarization mode were used. In the northeastern area of interest, temporary deforestation was detected, which had occurred in low lying areas due to prolonged flooding. The second area of interest, in the southeast, revealed man-made deforestation in high land areas on an immense scale due to the influx and settlement of seven hundred thousand refugees. The results of the two sub-studies demonstrate the applicability and need of SAR data to effectively monitor deforestation in Bangladesh especially as it allows isolating natural and anthropogenic deforestation