نتایج جستجو برای: resolution images from all classification approaches
تعداد نتایج: 7040853 فیلتر نتایج به سال:
Light fields are known for their potential in generating 3D reconstructions of a scene from novel viewpoints without need for a model of the scene. Reconstruction of novel views, however, often leads to ghosting artefacts, which can be relieved by correcting for the depth of objects within the scene using disparity compensation. Unfortunately, reconstructions from this disparity information suf...
The Landuse / Landcover system espoused by almost all Organisations and scientists, engineers and remote sensing community who are involved in mapping of earth surface features, is a system which is derived from the united States Geological Survey (USGS) LULC classification system. The application of RS and GIS involves determining of homogeneous zones, trend analysis of land use integration of...
Detailed land cover information is valuable for mapping complex urban environments. Recent enhancements to satellite sensor technology promise fit-for-purpose data, particularly when processed using contemporary classification approaches. We evaluate this promise by comparing the influence of spatial resolution, spectral band set and classification approach for mapping detailed urban land cover...
The growing use of Geographic Information Systems (GIS) has led to new research opportunities in the application of satellite imagery to urban analysis. The information content of such images is a function of the combined influence of the radiometric, spatial, and spectral resolution of the sensor. The different bands of satellite sensors are recorded synchronously so that their pixels may be p...
We present a novel method for creating high-resolution 3D reconstructions using RGB-D cameras, such as the Microsoft Kinect. We demonstrate how such a technique can be used both for large scale mapping and high-resolution object detection. Our work consists of two core contributions. First, we present an algorithm to generate 3D reconstructions of arbitrary resolution, up to that of the limitat...
Texture analysis plays an important role in image processing. Considering the extraordinary appearance texture sonar images, texture analysis are good choices for analysis of acoustic seabed images. Local binary pattern (LBP) operator is a very efficient and multi-resolution texture descriptor. It acquires appropriate information from the illumination and moods of images. Despite many developin...
The ability of recording the high resolution spectral signature of earth surface would be the most important feature of hyperspectral sensors. On the other hand, classification of hyperspectral imagery is known as one of the methods to extracting information from these remote sensing data sources. Despite the high potential of hyperspectral images in the information content point of view, there...
For land cover classification and urban area analysis remote sensing techniques are gaining more importance. Numerous remote sensing techniques have been developed for analyzing the satellite images. The launch of Worldview-2 satellite with resolution of 0.5 m signaled the advent of high resolution satellite images. Such images offer an exciting possibility for feature extraction as well as com...
Hyperspectral imaging with gathering hundreds spectral bands from the surface of the Earth allows us to separate materials with similar spectrum. Hyperspectral images can be used in many applications such as land chemical and physical parameter estimation, classification, target detection, unmixing, and so on. Among these applications, classification is especially interested. A hyperspectral im...
The monitoring of maritime areas with remote sensing is essential for security reasons and also for the conservation of environment. The synthetic aperture radar (SAR) can play an important role in this matter by considering the possibility of acquiring high-resolution images at nighttime and under cloud cover. Recently, the new approaches based on the sub-look analysis for preserving the infor...
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