Automatic Extraction of Man-Made Objects from Aerial and Space Images (II)

. Ed(s): Baltsavias, E. P.; Henricsson, O.

ISBN 10: 3764357886 / ISBN 13: 9783764357887

Published by Birkhauser Verlag AG, 1997

About this Item

This text contains contributions from around the world, which cover both theoretical and practical aspects of removing man-made objects (buildings, roads and so on) from digital aerial or satellite imagery. Editor(s): Baltsavias, E. P.; Henricsson, O. Series: Monte Verita. Num Pages: 405 pages, biography. BIC Classification: RGV; RGW; TTB; UYQV; UYS; UYT. Category: (P) Professional & Vocational. Dimension: 244 x 170 x 23. Weight in Grams: 752. . 1997. Hardback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9783764357887

Bibliographic Details

• Title: Automatic Extraction of Man-Made Objects from Aerial and Space Images (II)
• Publisher: Birkhauser Verlag AG
• Publication Date: 1997
• Language: English
• ISBN 10: 3764357886
• ISBN 13: 9783764357887
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.