The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Extraction of objects such as buildings from very high resolution(VHR) remote sensing imagery is an important task nowadays. In practical application, the extraction precision is normally satisfied through interactive manual input. Therefore, we propose a semi-automatic building extraction framework with an energy minimization model, which includes two stages: the first stage generates the coarse...
An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based active contour model (ACM) algorithm to achieve an efficient bilge dump detection tool. A threshold method was used to detect areas with a high bilge dump probability while the ACM method is used to get closed...
The parcel-based changed detection by adopting the holistic feature can extract the changed parcels in land-use maps[1]. This method of parcel-based change detection uses the holistic feature, which represents each land use parcels clipped by polygons in the land use map with the energy spectrum of WFT and extracts the changed parcels according to the distance threshold between feature vectors associated...
Navigation landmark features such as docks are often used in ships for localization and searching for shore targets during the voyage, which are of great economic and military significance. Continuous and complete dock data could hardly be extracted by existing coast dock extraction method, because the spatial relationships and other characteristics of dock are often ignored which only considers grayscale...
The inventory of economic forest planting on mountainous area is of great interest for the shareholders, ecologists, and governors. This study presents a novel object-based remote sensing image texture extraction method to aid the classification of mountain economic forest. Whereas the texture pattern of man-planted forest on mountainous area are similar with human fingerprint on remote sensing images,...
Change Vector Analysis (CVA) is an important change detection method for remote sensing imagery with medium and low resolution. Traditional CVA is a pixel-based method, which is insufficient for high-resolution (HR) imagery. An object-oriented change vector analysis method (OCVA) is proposed in the paper. Image segmentation method was used to get image objects. The object histogtam was extracted as...
This paper proposes a spatially constrained Bag-of-Visual-Words (BOV) method for hyperspectral image classification. We firstly extract the texture feature. The spectral and texture features are used as two types of low-level features, based on which, the high-level visual-words are constructed by the proposed method. We use the entropy rate superpixel segmentation method to segment the hyperspectral...
Local binary patterns (LBP) features extracted from hyperspectral imagery (HSI) have gained impressive performance in hyperspectral classification tasks, for which LBP got considerable attention. However, existing LBP-based hyperspectral imagery classification methods utilized two-dimensional LBP (2DLBP) that could capture gray variation signal in space, which did not excavate the contextual information...
The recent development in sensor technology shows the unprecedented growth of Remote Sensing (RS) data archives-Big Data. However, this growth in RS archives has resulted in many processing challenges. The three V's of big data- Volume, Velocity and Variety is highly relevant in situations such as flood, earthquake disaster, where real/near real time processing of data from different RS data sources...
In this paper, a method for road detection based on Duda and path operators has been presented. The roads are represented as slender dark regions with constant width and reflectance in the high-resolution SAR images. The path operators (path openings and closings) were performed as morphological filters in retaining linear structures. However, the filters were not sensitive to the width of linear...
As the development of marine economy and population explosion, coastal areas is suffering great pressure - because of the immigration from inland to the developed cities along east China. Island coastal zones, which is a specific ecosystem surrounded by the sea, is more sensitive to human activities, e.g. reclamations. It is essential to monitor the dynamic changes of the island coastal areas to retrieve...
The image registration is one of the key steps to achieve three-dimensional (3D) localization and the other image fusion processes. This article presents a registration method based on the combination of edge feature and corner feature. The processing steps include image segmentation, corner detection, edge detection, extraction of interested region, and correspondence points matching. The algorithm...
The very high resolution (VHR) images can be seen as multiview data. For better organizing and highlighting similarities and differences between the multiple views of data, a semisupervised multiview feature selection (SemiMFS) method is proposed in this paper, based on consensus and complementary principles. In SemiMFS, feature views are generated by decomposing features into multiple disjoint and...
It is significant for geological disasters detection from remote sensing image in emergency rescue. However, the automatic detection methods for geological disasters, depending only on low-level imagery features, generally result in low recognition precision. In practice, the most current extraction approaches of geological disasters are manual visual interpretation with the aid of experts' knowledge...
Remote sensing has been widely applied for environmental monitoring by means of change detection techniques, commonly for identifying deforestation signs which is the gateway for illegal activities such as uncontrolled urban growth and grazing pasture. Monthly acquired X-Band images from airborne Synthetic Aperture Radar (SAR) provided multi-temporal scenes employed in this work resulting in environmental...
This paper introduces a novel multi-layer line grouping method for perceptually building extraction from stereo aerial images. Nowadays, perceptual grouping algorithm for line features obtained from images has been widely investigated, but there are little attentions to be paid to building height information of the line segments applied in existing literature of edge grouping field. In order to enhance...
An algorithm for automatic recognition of overwater bridge target based on “joint feather and knowledge rule-based” is presented for the problem concerning automatic recognition of overwater bridge target in optical remote sensing images. Firstly, based on knowledge feathers of overwater bridge target, waters in an optical remote sensing image are extracted to narrow down bridge detection range. After...
Object-based image analysis (OBIA) provides a better solution for information extraction from high spatial resolution remote sensing image. Currently, selection of scale parameters is often dependent on subjective trial-and-error methods or post-evaluation of multi-segmentation, which directly reduces efficiency of land cover classification. This paper proposes a OBIA classification method combining...
In this paper, an unsupervised change detection model based on hybrid conditional random field model (HCRF) is proposed for high spatial resolution (HSR) remote sensing imagery. Traditional random field based algorithms are mainly based on the analysis of the difference image which ignores the spatial-temporal change information of ground objects which is important in dealing with HSR imagery. Thus...
Sparse representation-based classification (SRC) assigns a test sample to the class with minimal representation error via a sparse linear combination of all the training samples, which has successfully been applied to hyperspectral imagery (HSI). Meanwhile, spatial information, that means the adjacent pixels belong to the same class with a high probability, is a valuable complement to the spectral...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.