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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...
Polar lows (PLs), emerging over the sea ice edge, are studied using multisensor data information, surface analysis maps and reanalysis data. PLs over the Western (the Greenland, the Norwegian and the Barents Seas), and the Eastern (the Chukchi, the East Siberian and the Laptev Seas) parts of the Arctic are considered. It is shown that currently operating satellite instruments, taken separately, cannot...
In this paper, the blind restoration of a degraded image with an auxiliary image from another sensor is considered. In a typical multispectral satellite imaging system, multiple images from different sensors of the same area are available. When one of those images in a multiple image set is degraded, another image in the set can be used as a prior image for restoration. A hybrid algorithm based on...
Traditional approaches to structured semantic segmentation employ appearance-based classifiers to provide a class-likelihood at each spatial location and then post-process it with Markov Random Fields (MRF) to enforce label smoothness and structure in the output space. The spatial support for such techniques is usually a patch of pixels, which makes the prediction over-smoothed because the borders...
Multi-resolution analysis (MRA) has been successfully used in image processing with the recent emergence of applications to texture classification. Several studies have investigated the discriminating power of wavelet-based features in various applications such as image compression, image denoising, and classification of natural textures. Recently, the curvelet and contourlet transforms have emerged...
It is highly necessary to merge high spatial resolution panchromatic images with high spectral resolution multispectral images in image processing tasks and thematic applications. WorldView-3 (WV-3) imagery was investigated for generating pan-sharped multispectral imagery. Brovey and NNDiffuse pan sharpening algorithms were comparatively used to perform the image fusion and the quality was also assessed...
The effects of shadow correction on the classification of vegetation and land cover is studied in high resolution (10 × 10 cm) aerial images. Shadow detection reuses the feature set derived from the imagery for vegetation classification. A separate model is used to classify data in the first pass into three classes: water, land and shadows. Areas classified as shadow are then corrected using a regression...
Invalid image pixels often cluster within the overlapping region of neighboring Landsat scenes and can have negative impact on the quality of image composites generated from multiple Landsat scenes. We propose a method to automatically screen invalid image pixels in Landsat-4, 5, 7 images by generating a polygon smaller than the bounding box of each scene. Our assessment results show that masking...
This paper presents a new method for polarimetric synthetic aperture radar (PolSAR) image classification. Firstly, to get a reasonable edge strength map, polarimetric information is used in edge strength calculation, and watershed algorithm is used to obtain the oversegmentation using the edge strength. Secondly, a searching table is used to determine the most suitable region to be merged. Finally,...
Nowadays, the accidents of oil spill become more and more frequent, causing pollution to the natural resources, marine environment and lives in the sea. As a result, the detection of oil spill draws more and more attentions. One of the most popular region-based active contour models proposed by Chan and Vese, is widely used to image segmentation. But it can't segment hyperspectral oil spill image...
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 new advanced very high resolution (VHR) synthetic aperture radar (SAR) sensors are capable of achieving sub-meter resolution, which offers the opportunity for a fine level of analysis of man-made structures. In this paper, we present a method for the detection and 2-D reconstruction of building radar footprints from VHR SAR scenes. The method is based on the extraction of a set of low-level features...
In image processing, the detection of keypoint plays a significant role in foundation work of many image applications. Most widely distributed features in images are corners. Among the famous corner detectors, Harris detector has shown its excellent performance. However, when coming up with SAR image, the speckle noise may severely influence the performance of Harris. And Harris is seldom used in...
A probability graph model can effectively model spectral and spatial dependencies within remote sensing images for land cover classification. The most common structure used to unify this probabilistic information is a second order Markov network that encapsulate unary and pairwise potentials. In this paper we explore various heuristics to discover new graph structures that will assist with classifying...
Markov random field (MRF)based spatial regularizing methodology can improve the maps by imposing a spatial smoothness prior on the image grid, but also leads to oversmoothing at image boundary areas. This problem is caused by the reason that classic isotropous smoothness prior cannot take local discontinuities into account. In this context, this paper proposes a novel two-step MRF regularization algorithm,...
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...
Speckle noise is an inherent problem in synthetic aperture radar (SAR) images. Recently, non-local (NL) means performs well in speckle reduction. However, there exist two issues in traditional NL means. Speckle noise and strong targets would affect the correctness, thus resulting in over smoothing and speckles unchanged. In this paper, an improved algorithm combined with wavelet transform and adaptive...
Combing the trait that the building outline can be reflected in high resolution DSM data, the extraction method of building top and the edge point of building top is studied based on region growing Algorithm, and then the edge point is tracked in vectorization. The regularization processing method toward the regular building and circular building is researched based on the classification of construction...
Land-cover and land-use semantic labeling in centimeter resolution imagery (ultra-high resolution) is mostly performed by supervised classification of informative descriptors extracted from spatially coherent but small objects (e.g. superpixels or patches). In this paper, we propose an extension of this reasoning by proposing a class-specific, multi-scale and bottom-up object proposal strategy to...
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