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Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry
Author(s) -
Fraser Clive S.,
Woods Alex,
Brizzi Danny
Publication year - 2005
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/j.1477-9730.2005.00327.x
Subject(s) - photogrammetry , redundancy (engineering) , computer vision , computer science , artificial intelligence , metrology , intersection (aeronautics) , total station , data redundancy , geography , optics , cartography , physics , operating system
A generic network design in close range photogrammetry is one where optimal multi‐ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ = 0·065 mm, or 1/400 000 of the diameter of the reflector.