作者：
Garcia-Consuegra, J.Cisneros, G.Martinez, A.
Castilla-La Mancha University Campus Universitario s/n 02071 Albacete Spain Grupo de Tratamiento de Imágenes
Universidad Politécnica de Madrid Ciudad Universitaria 28040 Madrid Spain
Castilla-La Mancha University Campus Universitario s/n 02071 Albacete Spain
In this paper we provide a solution to a common problem in remotesensing when woody crops (almond and olive fields, vineyards, and so on) must be located and discriminated. Experience has taught us that, currently, t...
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Thermal hyperspectral imagery introduces new possibilities in remotesensing. This paper deals with testing the accuracy of the supervised classification of the artificial objects in the thermal hyperspectral imagery,...
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As a data structure, a tree is an optimal presentation of hierarchical objects. Many irregular and dynamical phenomena studied for example in biology, medical sciences, meteorology, and geomorphology can be modelled a...
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Hyperspectral image sets are three dimensional data volumes that are difficult to exploit by manual means because they are comprised of multiple bands of image data that are not easily visualized or assessed. GTE Gove...
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Hyperspectral image sets are three dimensional data volumes that are difficult to exploit by manual means because they are comprised of multiple bands of image data that are not easily visualized or assessed. GTE Government Systems Corporation has developed a system that utilizes Evolutionary Computing techniques to automatically identify materials in terrain hyperspectral imagery. The system employs sophisticated signature preprocessing and a unique combination of non-parametric search algorithms guided by a model based cost function to achieve rapid convergence and patternrecognition. The system is scaleable and is capable of discriminating and identifying pertinent materials that comprise a specific object of interest in the terrain and estimating the percentage of materials present within a pixel of interest (spectral unmixing). The method has been applied and evaluated against real hyperspectral imagery data from the AVIRIS sensor. In addition, the process has been applied to remotely sensed infrared spectra collected at the microscopic level to assess the amounts of DNA, RNA and protein present in human tissue samples as an aid to the early detection of cancer.
The AMOVIP project is a joint initiative for a cooperation in specific aspects of vision research and their applications, involving EU partners in Spain and Portugal together with developing countries Mexico and Brazi...
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Mathematical morphology coupled with creation of a time stack image and principal oscillation pattern analysis are used to determine the water depths over a known sloping bottom from synthetic remotely sensed images. ...
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In the field of remotesensing, image-based object recognition can benefit from direct measurement of characteristic dimensions. But in many cases image resolution and collateral data about the mapping properties do n...
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ISBN:
(纸本)081943194X
In the field of remotesensing, image-based object recognition can benefit from direct measurement of characteristic dimensions. But in many cases image resolution and collateral data about the mapping properties do not provide sufficient precision for the intended purposes of object identification. In such cases the recognition performance can often be increased significantly by coupling several characteristic dimensions and taking their mutual relations into account. The approach proposed in this paper defines so-called "keypoint models" that describe certain object classes by the geometrical arrangement of characteristic features, denoted as keypoints. A feature space is spanned by the normalized distances of these keypoints. The complexity of the models as expressed by the number of keypoints is scalable and gets selected according to the specific recognition needs. Different model variants cover the significance of object features according to the spectral sensitivity of the sensor. Keypoints are intended to be marked interactively by an image analyst while taking into account the inaccuracies caused by image resolution and other possible ambiguities. We demonstrate our approach in the example domain of airplanes where the complexity of our actually most sophisticated model amounts to ten keypoints. We place special emphasis on the aspects of intuitive usability for image analysts working under time pressure. Perspectives of integrating automatic feature-extraction techniques are also discussed briefly.
This paper aims at presenting a study of costs and performance concerning different multimedia communication techniques that can be employed in the context of the implementation of 2/sup nd/ generation remote video-su...
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This summary aims at presenting an overview of the CEC-ESPRIT AVS-RIO (Advanced Video Surveillance - Cable Television-Based remote Video surveillance System for Protected sites Monitoring) project. The peculiarity of ...
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High spectral remotesensing is a hopeful technology in diagnosing crop nutrition background. With surface spectral measurement and laboratory biochemical analysis, the relationship between crop properties and spectra...
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High spectral remotesensing is a hopeful technology in diagnosing crop nutrition background. With surface spectral measurement and laboratory biochemical analysis, the relationship between crop properties and spectral remotesensing data has been established. Seven chemical components - total chlorophyll, water crude protein, soluble sugar, N, P, K - were analyzed by laboratory chemical analyzing instrument. Foliar spectral property was detected outdoors by surface spectrometer. Chemical concentrations have been related to foliar spectral properties through stepwise multiple regression. The statistical equations between the chemical concentrations and reflectance as well as its several transformations were established. They underscored good estimation performance for chlorophyll, water crude protein, N and K with high squared multiple correlation coefficients (R2) values and high believable level (>95%). Especially R2 value of the equation between crude protein concentration and the first derivative of reflectance is 0.9564, which is the best result in the study of the fresh leave biochemistry up to now. On the basis of field experiment, an airborne remotesensing for crop nutrition monitoring was conducted in Shunyi County, Beijing, P.R. China. The sensor, made by Chinese Academy of Sciences, is in visible and near infrared band. By imageprocessing, the crop biochemistry map is obtained.
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