Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-09T19:35:07.793Z Has data issue: false hasContentIssue false

5 - Geometric registration

Published online by Cambridge University Press:  30 October 2009

Jean-Luc Starck
Affiliation:
Centre Commissariat à l'Energie Atomique (CEA), Saclay
Fionn D. Murtagh
Affiliation:
University of Ulster
Get access

Summary

Image registration of remotely sensed data is a procedure that determines the best spatial fit between two or more images that overlap the same scene, acquired at the same time or at different times, by identical or different sensors. This is an important step, as it is frequently necessary to compare data taken at different times on a point-to-point basis, for many applications such as the study of temporal changes for example. Therefore we need to obtain a new dataset in such a way that its image under an appropriate transform is registered, geometrically, with previous datasets.

The inventory of natural resources and the management of the environment requires appropriate and complex perception of the objects to be studied. Often a multiresolution approach is essential for the identification of the phenomena studied, as well as for the understanding of the dynamical processes underlying them. In this case, the processing of data taken with different ground resolutions by different or identical sensors is necessary.

Another important situation where the need for different images acquired with a different ground resolution sensor arises is when the generalization to larger surface areas of an identification or an interpretation model, based on small areas, is required (Achard and Blasco, 1990). This is the case for studies on a continental scale. Examples of this application can be found in Justice and Hiernaux (1986), Hiernaux and Justice (1986) and Prince, Tucker and Justice (1986). Therefore, the data must be geometrically registered with the best possible accuracy.

Type
Chapter
Information
Image Processing and Data Analysis
The Multiscale Approach
, pp. 152 - 184
Publisher: Cambridge University Press
Print publication year: 1998

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×