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Item Details
| Title:
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MACHINE VISION AND ADVANCED IMAGE PROCESSING IN REMOTE SENSING
PROCEEDINGS OF CONCERTED ACTION MAVIRIC (MACHINE VISION IN REMOTELY SENSED IMAGE COMPREHENSION) |
| By: |
Ioannis Kanellopoulos (Editor), G. G. Wilkinson (Editor), Theo Moons (Editor) |
| Format: |
Hardback |
| List price:
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£109.99 |
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We believe that this item is permanently unavailable, and so we cannot source
it.
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| ISBN 10: |
3540655719 |
| ISBN 13: |
9783540655718 |
| Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
| Pub. date: |
20 May, 1999 |
| Edition: |
1999 ed. |
| Pages: |
335 |
| Description: |
This work describes some of the late-1990s developments in the techniques for the analysis of remotely sensed satellite imagery. It explores the increasing links between computer vision and remote sensing, and includes chapters from authors working in the two fields. |
| Synopsis: |
Since 1994, the European Commission has undertaken various actions to expand the use of Earth observation (EO) from space in the Union and to stimulate value-added services based on the use of Earth observation satellite data.' By supporting research and technological development activities in this area, DG XII responded to the need to increase the cost-effectiveness of space- derived environmental information. At the same time, it has contributed to a better exploitation of this unique technology, which is a key source of data for environmental monitoring from local to global scale. MAVIRIC is part of the investment made in the context of the Environ- ment and Climate Programme (1994-1998) to strengthen applied techniques, based on a better understanding of the link between the remote sensing signal and the underlying bio- geo-physical processes. Translation of this scientific know-how into practical algorithms or methods is a priority in order to con- vert more quickly, effectively and accurately space signals into geographical information. Now the availability of high spatial resolution satellite data is rapidly evolving and the fusion of data from different sensors including radar sensors is progressing well, the question arises whether existing machine vision approaches could be advantageously used by the remote sensing community. Automatic feature/object extraction from remotely sensed images looks very attractive in terms of processing time, standardisation and implementation of operational processing chains, but it remains highly complex when applied to natural scenes. |
| Illustrations: |
13 Tables, black and white; X, 335 p. |
| Publication: |
Germany |
| Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
| Returns: |
Returnable |
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