Describes a novel technique for the detection of unusual events in remote sensed imagery when the images contain a high level of background clutter. The technique combines conventional imageprocessing algorithms with...
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Describes a novel technique for the detection of unusual events in remote sensed imagery when the images contain a high level of background clutter. The technique combines conventional imageprocessing algorithms with statistical methods to derive simple models of image backgrounds. These fractal-based models have been shown experimentally to give a good fit to statistics derived from remote sensed imagery of structured natural backgrounds such as mountain ranges and the sea surface. Unusual events, such as man-made objects show statistics that differ markedly from the background models and can be detected by finding differences between measured image statistics and the assumed background model.< >
Whenever electromagnetic radiation is reflected from a surface, it becomes polarised to a degree, dependent upon surface structure, texture and angle of incidence. If the polarisation information from the reflected ra...
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Whenever electromagnetic radiation is reflected from a surface, it becomes polarised to a degree, dependent upon surface structure, texture and angle of incidence. If the polarisation information from the reflected radiation is extracted from conventional intensity information by an imaging polarimeter it is possible to reveal detail about the surface that cannot be obtained by any other imaging technique. Hence, polarimetric images provide the means of observing objects and phenomena that are invisible to conventional imaging systems. An imaging polarimeter produces images representing the spatial variation in polarisation over the scene, which can be related to true texture, surface structure and material type. To date, polarimetric imagery has been completely neglected as a powerful, nonintrusive visual probing tool. Therefore, to provide an adequate perspective on the remotesensing capability of an imaging polarimeter, and how polarimetry could become an important technique for visual probing, the relevant theoretical basis for the processing of polarimetric images is presented.< >
Discusses the relation between differential propagation phase shift Delta Phi and rainrate R, which is found to be nearly linear and be almost insensitive to the dropsize distribution parameters. The studies show that...
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Discusses the relation between differential propagation phase shift Delta Phi and rainrate R, which is found to be nearly linear and be almost insensitive to the dropsize distribution parameters. The studies show that by using Delta Phi method, we can extract rainrates from CDR radar and correct propagation effects on CDR radar data. It is clear that the technique of differential propagation phase shift can be applied as a potential tool to improve measurements of precipitations in remotesensing.< >
Although remotesensing is generally associated with satellite imagery, it can also be applied to sea-floor imagery collected by acoustic surveying techniques. Sea-floor surveying is important in environmental and oce...
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Although remotesensing is generally associated with satellite imagery, it can also be applied to sea-floor imagery collected by acoustic surveying techniques. Sea-floor surveying is important in environmental and oceanographic research, and for mineral prospecting and marine civil engineering projects. The main instrument for sea-floor mapping is the side-scan sonar. This generates an image of the sea-floor by recording the backscattered energy at shallow grazing angles from a short acoustic pulse, which is transmitted along a fan shaped beam, narrow in azimuth but wide in elevation. Typical carrier frequencies are in the region of 100 kHz and chirp sources are becoming available. Seismic profiling is used to obtain information of the sub-bottom by transmitting an acoustic pulse into the seabed and recording the reflected signals. The seismic sensor looks directly downwards at the sea-floor and operates at much lower frequencies, typically 1-3 kHz. This paper is confined to the classical remotesensing problems of delineating boundaries between different regions of the images and classifying the domains within these boundaries.< >
As the volume of data collected by an increasing number of satellites escalates, it has become of paramount importance that methods of coping with and making best use of this information are developed. Current trends ...
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As the volume of data collected by an increasing number of satellites escalates, it has become of paramount importance that methods of coping with and making best use of this information are developed. Current trends are moving towards automatic and knowledge-based analysis systems particularly for monitoring applications where the same kinds of interpretation task must be repeated many times. The MuSIP project, part funded by the European ESPRIT programme for research information, aims to develop a software demonstrator for the automatic fusion and analysis of multisource data. The project recognises this need across all computer vision applications and so will test the demonstrator on two dissimilar applications, one in the field of remotesensing and one in the field of medical image analysis. The target remotesensing application is the monitoring of forestry using a dataset of radar and optical imagery, map and ground data. This paper introduces the modules that comprise the demonstrator that is: a supervisor with its associated knowledge bases, algorithms and the databases. Attention is focussed in particular on the role of knowledge bases and the methods of data fusion.< >
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