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With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the e...
In this paper a method for automatic extraction of building roof boundaries is proposed, which combines LiDAR data and highresolution aerial images. The proposed method is based on three steps. In the...
Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land ...
Digital Elevation Models (DEMs) are considered as one of the most relevant geospatial data to carry out land-cover and land-use classification. This work deals with the application of a mathematical f...
This study applies remote sensing technology combined with Markov Process to monitor and forecast the dynamic change of forest resource in Chinese Loess Plateau. At first, according to the dynamic cha...
The information in a pixel of satellite data within the instantaneous Field of View (IFOV) of the sensor is a mixture of different land cover types, and the individual land cover components can be est...
In this paper, a methodology is proposed for the geometric refinement of LiDAR building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology...
Traffic observation from airplane platforms using digital cameras is a fairly new application of Video Image Detection Systems (VIDS). These systems are also particularly interesting for observations ...
In this paper we describe a new concept for the reconstruction of buildings. In contrast to most of the published approaches, we link the reconstruction process with the building interpretation. With ...
This paper introduces the principle of genetic algorithm and the basic method of solving Markov Random Field parameters. Focusing on the shortcoming in present methods, a new method based on genetic a...
Information technology is increasingly used to support civil infrastructure systems that are large, complex heterogeneous, and distributed. These dynamic systems include communication systems, roads, ...
Markov random field (MRF) is an effective method for description of local spatial-temporal dependence of image and has been widely used in land cover classification and change detection. However, ex...
The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Markov Random Fields (MRF) approach to this problem, a ...
MRF model is recognized as one of efficient tools for image classification. However, traditional MRF model prove to be limited for high resolution image classification. This paper presents a joint pix...

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