The problem of Map-matching is one key problem in the field of aircraft and vehicle guidance. It deals with the technologies of remotesensing, computer vision, imageprocessing and patternrecognition, etc. Researche...
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ISBN:
(纸本)0819442836
The problem of Map-matching is one key problem in the field of aircraft and vehicle guidance. It deals with the technologies of remotesensing, computer vision, imageprocessing and patternrecognition, etc. Researchers are focusing on how to improve the system's performance, to reduce the searching times and error matching probability [1]. With using an improved quadtree image representative method and the idea of the sequential similarity detection algorithm (SSDA), a hierarchical map-matching algorithm based on embedded MPP system is designed in this paper. The algorithm can greatly reduce matching times and improve locate accuracy.
This contribution describes a new approach for detection of shadow areas appearing in remotesensingimage data. Identification of objects like streets or vehicles is frequently disturbed by illumination effects like ...
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ISBN:
(纸本)0780367154
This contribution describes a new approach for detection of shadow areas appearing in remotesensingimage data. Identification of objects like streets or vehicles is frequently disturbed by illumination effects like hard shadows or inhomogenous darkening due to varying tilt angles of the processed terrain. To increase the reliability of the recognition process, we apply a sensor fusion of elevation data from laserscanning and optical image data. The represented algorithm improves the results iteratively. The different results are discussed and then used for further processing within a radiometric equalization.
A novel approach to the automatic classification of remote sensed images is proposed. This approach is based on a three-phase procedure: first pixels which belong to the areas of interest with large likelihood are sel...
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ISBN:
(纸本)0769511848
A novel approach to the automatic classification of remote sensed images is proposed. This approach is based on a three-phase procedure: first pixels which belong to the areas of interest with large likelihood are selected as seeds;second the seeds are refined into connected shapes using two well known imageprocessing techniques;third the results of the shape refinement algorithms are merged together The initial seed extraction is performed using a simple thresholding strategy applied to NDVI4-3 index. Subsequently shape refinement through Seeded Region Growing and Watershed Decomposition is applied, finally a merging procedure is applied to build likelihood maps, Experimental results are presented to analyze the correctness and robustness of the method in recognizing vegetation areas around Mount Etna.
An automatic accurate recognition scheme for large-scale structures such as ocean currents, eddies and water masses is an essential technology for extracting environmental information and fishing resource. In this pap...
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ISBN:
(纸本)0819441864
An automatic accurate recognition scheme for large-scale structures such as ocean currents, eddies and water masses is an essential technology for extracting environmental information and fishing resource. In this paper, new autonomous recognition schemes based on knowledge-base approaches are derived. And a fundamental scheme for enabling processing to be carried out by small-scale computer architectures is developed. These schemes can greatly reduce the amount of data required to describe large-scale structures like ocean eddies and/or ocean currents, and are therefore expected to be very useful for the autonomous on-orbit processing of ocean observation data. Some applications of the schemes to the recognition of moving shapes in noisy images remotely sensed from Earth orbits are also presented with evaluative experimental results.
作者:
Li, YPeng, JHuazhong Univ Sci & Technol
State Educ Commiss Lab Image Informat & Intellige Inst Pattern Recognit & Artificial Intelligence Wuhan Peoples R China
A new algorithm to estimate Hurst parameter is introduced in this work A remotesensing texture is modeled as a fBm process. Since fBm is characterized by only one Hurst parameter, it is not flexible enough to model t...
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ISBN:
(纸本)081944278X
A new algorithm to estimate Hurst parameter is introduced in this work A remotesensing texture is modeled as a fBm process. Since fBm is characterized by only one Hurst parameter, it is not flexible enough to model the short-term correlation structure. Therefore extended models were proposed to settle this problem. Noting that the track of the logarithm delta variances is certain, and the slopes k(s) of the piecewise lines characterize the specific texture, we use k(s)/2 to estimate the multiscale Hurst parameters of the digital image. Since the new features characterize the textures in a multi-scale way and meet with the characters of the natural processes, they perform better than the existing features based on fractal models and wavelet transforms.
作者:
Li, YPeng, JHuazhong Univ Sci & Technol
State Educ Commiss Lab Image Informat & Intellige Inst Pattern Recognit & Artificial Intelligence Wuhan Peoples R China
The recognition method for the harbor contour is presented in this paper. The chain code of the contour represents the orientation and the curvature of the contour, and from it the control points are detected by the e...
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ISBN:
(纸本)081944278X
The recognition method for the harbor contour is presented in this paper. The chain code of the contour represents the orientation and the curvature of the contour, and from it the control points are detected by the extra of wavelet transform. The primitive of the harbor contour is composed of four consecutive control points satisfying certain criteria. Three features of the primitive, which are scale- and rotation- invariant, and the deduced recognition rule, with the form of shape energy, are described in the paper.
In order to move towards a more adequate classification methodology one issue that has received particular attention within the remotesensing community is the development of soft classification models in alternative ...
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ISBN:
(纸本)081943826X
In order to move towards a more adequate classification methodology one issue that has received particular attention within the remotesensing community is the development of soft classification models in alternative to conventional hard classification techniques. In soft classification, pattern indeterminacy must be connected with different forms of uncertainty such as vagueness, ambiguity, resulting in gradual strength of membership to classes. The work is focused on the use of soft classification techniques for production of soft maps in which grades of membership to classes are the final meaningful outputs. When soft land cover maps are generated, grades of membership are correlated to the percentages of coverage;when maps specifying more abstract themes are generated grades have to represent the human natural approximation with which patterns matches with cognitive categories. Despite the availability of several soft classification techniques, soft thematic mapping has not being very often employed and the majority of classifications are still based on hard paradigms and maps are presented in discrete form. Significant problems in the use of these techniques limit their diffusion. The aim of this paper is to analyze the above limitations in an attempt of contributing to their overcoming.
The approach to the detection of fires suggested here is based on methods of patternrecognition in spaces of the informative parameters from information contained in indirect measurements, which in this case are five...
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ISBN:
(纸本)0819438278
The approach to the detection of fires suggested here is based on methods of patternrecognition in spaces of the informative parameters from information contained in indirect measurements, which in this case are five-channel videodata recorded with the AVHRR instrument placed onboard NOAA satellites. A problem of preliminary integrated normalization of satellite videodata, including a transition to constant dimensions of scanning spot projections on the Earth's surface, an increase in the spatial resolution of images for a model of integration within the spot, and correction of the radiobrightness characteristics of the images, is considered. Normalized images are subsequently used to solve the problem of detecting small-sized fires with the help of a three-stage procedure by an algorithm of patternrecognition in space of the informative parameters. A natural criterion for estimating the information content for the class of detection and patternrecognition problems is the functional of the average risk. In this case, the informative set of parameters and the decision rule are found by minimization of this functional. Because conditional probability densities, being mathematical models of stochastic images, are unknown, the problem of reconstructing distributions based on teaching samples with the use of nonparametric estimates with modified Epanechnikov kernel is solved. Unknown parameters of distributions are determined by minimization of a functional of the empirical risk. A comparison between the results of operation by the algorithm and the operator work demonstrates high efficiency of the algorithm of detecting thermal anomalies of fire types.
A new method to decompose digital remotely sensed image is discussed in this paper. The information in original remotely sensed data can be decomposed, pixel-by-pixel, into three components of natural light - solar di...
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ISBN:
(纸本)7900081585
A new method to decompose digital remotely sensed image is discussed in this paper. The information in original remotely sensed data can be decomposed, pixel-by-pixel, into three components of natural light - solar direct illuminance (SDI), sky-scattering illuminance (SSI) and atmospheric path radiance (APR). Because the remotely sensed information is the result of the interaction between each component and ground features, the resultant component images of this method are more powerful than the original remotely sensed data in the quantitative inversion research of ground radiation energy, atmospheric environment condition, and remotesensingimagepatternrecognition.
This paper presents a knowledge-based approach for automatic 3D building reconstruction. By combining the aerial image analysis with information from GIS maps and domain specific knowledge the complexity of the buildi...
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ISBN:
(纸本)076951183X;0769511848
This paper presents a knowledge-based approach for automatic 3D building reconstruction. By combining the aerial image analysis with information from GIS maps and domain specific knowledge the complexity of the building reconstruction process can be greatly reduced. The building reconstruction process is described as a tree search in the space of possible building hypotheses. To guide the search of the tree an evaluation function based on mutual information is defined. This evaluation function allows comparison of different building hypotheses obtained by applying a fitting algorithm. The performance of the 3D reconstruction is improved by incorporating geometric constraints.
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