A. Cross's research while affiliated with University of Reading and other places
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Publications (6)
This paper describes the application of an image segmentation technique to remotely-sensed terrain images used for environmental monitoring. The segmentation is a preprocessing operation which is applied prior to image classification in order to improve classification accuracy from that achievable by classifying pixels individually on the basis of...
To interpret remotely sensed data accurately, a variety of information is required about the sensor, the sensing conditions, the scene and the application. At present a good interpretation can only be achieved by a photointerpreter, unless the problem is small and can be well defined. To exploit to the full the wealth of satellite data available, e...
Remotely-sensed data constitute a major potential source of input to geographical information systems (GIS)However, these data often have a relatively poor classification accuracy compared with that of the cartographic data from maps with which they may be combined in the course of GIS analysis. The possibility exists of using data sets (in the for...
The increasing volume of remotely-sensed data has led to a need for efficient automatic analysis procedures. A system is presented for automatic, knowledge-based segmentation of remotely-sensed images of the land. The system uses the information in time sequences of remotely-sensed data together with cartographic map data and domain expertise to bu...
In order to cope with the large volume of remotely-sensed data available now and expected in the future, efficient automatic processing techniques are required. A particular problem in automatic interpretation of this data is the identification of relevant connected regions in the image, i.e. segmentation. This can generally only be achieved to a r...
The paper describes progress on a UK Alvey Information Technology project to develop a system for the knowledge-based segmentation and interpretation of remotely-sensed images. The knowledge used may be about the types of structures to be expected within the scene and their relationships, and other datasets such as existing map data or previous cla...
Citations
... As a result of poor resolution, it is often necessary to employ sophisticated scene understanding techniques to aid in the interpretation of images with the end results being very dependent on the techniques chosen; for example see [3] and [4]. It is clear that there is no single 'best' interpretation that will suit all subsequent user requests, but rather that the interpretation can only be constructed accurately when the use that it will be put to is known beforehand [5]. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/278619042664459-1443439364272_Q64/David-Hogg.jpg)
... The images were printed as black and white composite or individual bands (3) . Later, the classification was done through knowledge-based systems in which the pre-defined rules were programmed into software products that classified land areas into different cover type (9,10) . With the start of this millennia machine learning (ML) and pattern recognition (PR) systems have emerged as the leading approach for satellite image classification (11,12) . ...
... Le terme « objet » désigne un groupe de pixels contigus. La segmentation est basée sur des paramètres prédéfinis comme la compacité, la forme et l'échelle, dérivés de la connaissance du monde réel des caractéristiques que l'on veut identifier (Mason et al., 1988). Dans une deuxième étape, chaque objet (segment) est classé sur la base d'une ou plusieurs propriétés statistiques des pixels contenus. ...
... A split and merge technique can be used to create regions of constant tone. Regions can also be grown from seed pixels (Cross, Dury, and Mason 1988). ...
... Atsushi Imiya Chiba University, Japan Recollection of Maria Petrou at University of Reading Maria Petrou joined the NERC Unit for Thematic Information Systems (NUTIS) in the Department of Geography in Reading University on a one-year research fellowship in 1986 [7] ...
Reference: Homage to Professor Maria Petrou
