The field of wavelets has opened up new opportunities;for the compression of satellite sensor imagery. This paper examines the influence of wavelet compression on the automatic classification of urban environments. Ai...
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ISBN:
(纸本)0769507514
The field of wavelets has opened up new opportunities;for the compression of satellite sensor imagery. This paper examines the influence of wavelet compression on the automatic classification of urban environments. Ail borne laser scanning data is introduced as an additional channel alongside the spectral channels of colour infrared imagery. This effectively integrates the local height and multi-spectral information sour-ces. To incorporate conte,ut information, the feature base is expanded to include both spectral and non-spectral features. A maximum likelihood classification approach is then applied. It is demonstrated that the classification of urban scenes is considerably improved by fusing multi-spectral and geometric data sets. The fused imagery is then systematically compressed (channel by channel) at compression rates ranging from 5 to 100 using a wavelet-based algorithm. The compressed imagery is then classified using the approach described here-above. Analysis of the results obtained indicates that a compression rate of up to 20 can convieniently be employed without adversely affecting the segmentation results.
The aim of our report is to show the possibility of mathematical modeling of patternrecognition as information processing in human memory Mathematical model of information processing in human memory for description s...
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WE have developed a novel visual sensing system that monitors respiration for 24 hours non-restrictively. The principle of the system is inter-image subtraction. Compared with conventional methods, the system has adva...
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ISBN:
(纸本)0769507506;0769507514
WE have developed a novel visual sensing system that monitors respiration for 24 hours non-restrictively. The principle of the system is inter-image subtraction. Compared with conventional methods, the system has advantages which make it suitable for a long-term monitoring: 1) patients experience no physiological burden during sleep, 2) no manual operation is necessary since at has self-optimizing functions for imageprocessing and 3) it judges patient's sleep condition adequately using statistical analysis. The system thus can be applied to predict abnormality of health conditions, and thus for example, alert care providers so that action can be taken with a view to preventing the sudden death of elderly people or, in case of children, to prevent occurrence of sudden infant death syndrome. It can be also applied to the detect clinically dangerous sleep apnea syndrome. Experimental results in a nursing home for the aged have shown the efficiency of the system.
Over the past years, digital imagery applications had a strong growth. In scientific fields, this technology is fast becoming mainstream in many applications and is implanted solidly in remotesensing domain. This fac...
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In the year 1996 Aero-sensing Radarsysteme GmbH designed and manufactured the AeS-1 airborne X-band Interferometric Synthetic Aperture Radar (InSAR) system, capable of generating images with a ground resolution up to ...
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The goal of this paper is twofold. First, we present a supervised fuzzy c-mean (SFCM) classifier for the classification of high dimensional data. Comparisons with conventional FCM clustering technique and Bayesian cla...
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In the field of patternrecognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification systems. However, previous work clear...
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In the field of patternrecognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification systems. However, previous work clearly showed that such image classification systems are effective only if the neural networks forming them make different errors. Therefore, the fundamental need for methods aimed to design ensembles of "error-independent" networks is currently acknowledged. In this paper, an approach to the automatic design of effective neural network ensembles is proposed. Given an initial large set of neural networks, our approach is aimed to select the subset formed by the most error-independent nets. Reported results on the classification of multisensor remote-sensingimages show that this approach allows one to design effective neural network ensembles.
A study of spectropolarization contrasts of natural backgrounds and artificial objects is presented. In remotesensing, polarization measurement and brightness measurement supplement one another for identification of ...
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A study of spectropolarization contrasts of natural backgrounds and artificial objects is presented. In remotesensing, polarization measurement and brightness measurement supplement one another for identification of objects. But using one or another composite image for target recognition depends on image gain conditions.
This paper describes a new approach for semi-automatic building reconstruction integrated in hybrid photogrammetric adjustment. The new method uses a unique way of modelling building primitives by boundary representat...
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The general trend in remotesensing is on one hand to increase the number of spectral bands and the geometric resolution of the imaging sensors which leads to higher data rates and data volumes. On the other hand the ...
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ISBN:
(纸本)0819437778
The general trend in remotesensing is on one hand to increase the number of spectral bands and the geometric resolution of the imaging sensors which leads to higher data rates and data volumes. On the other hand the user is often only interested in special information of the received sensor data and not in the whole data mass. Concerning these two tendencies a main part of the signal pre-processing can already be done for special users and tasks on-board a satellite. For the BIRD (Bispectral InfraRed Detection) mission a new approach of an on-board data processing is made. The main goal of the BIRD mission is the fire recognition and the detection of hot spots. This paper describes the technical solution, of an on-board image data processing system based on the sensor system on two new IR-Sensors and the stereo line scanner WAOSS (Wide-Angle-Optoelectronic-Scanner). The aim of this data processing system is to reduce the data stream from the satellite due to generations of gee-coded thematic maps. This reduction will be made by a multispectral classification. For this classification a special hardware based on the neural network processor NI1000 was designed. This hardware is integrated in the payload data handling system of the satellite.
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