Paper
10 May 2012 Automatic and generic mosaicing of multisensor images: an application to Pleiades HR
F. Bignalet-Cazalet, S. Baillarin, D. Greslou
Author Affiliations +
Abstract
In the early phase of the Pleiades program, the CNES (the French Space Agency) specified and developed a fully automatic mosaicing processing unit, in order to generate satellite image mosaics under operational conditions. This tool can automatically put each input image in a common geometry, homogenize the radiometry, and generate orthomosaics using stitching lines. As the image quality commissioning phase of Pleiades1A is on-going, this mosaicing process is being tested for the first time under operational conditions. The French newly launched high resolution satellite can acquire adjacent images for French Civil and Defense User Ground Segments. This paper presents the very firsts results of mosaicing Pleiades1A images. Beyond Pleiades' use, our mosaicing tool can process a significant variety of images, including other satellites and airborne acquisitions, using automatically-taken or external ground control points, offering time-based image superposition, and more. This paper also presents the design of the mosaicing tool and describes the processing workflow and the additional capabilities and applications.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
F. Bignalet-Cazalet, S. Baillarin, and D. Greslou "Automatic and generic mosaicing of multisensor images: an application to Pleiades HR", Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 84070M (10 May 2012); https://doi.org/10.1117/12.918013
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image processing

Satellites

Image registration

Satellite imaging

Earth observing sensors

Image quality

Image segmentation

Back to Top