Paper Info
Title
Context-sensitive pan-sharpening of multispectral images
Abstract
Multiresolution analysis (MRA) and component substitution (CS) are the two basic frameworks to which image fusion algorithms can be reported when merging multi-spectral (MS) and panchromatic (Pan) images (Pan-sharpening). State-of-the-art algorithms add spatial details derived from the Pan image to the MS bands according to an injection model. The capability of the model to describe the relationship between the MS and Pan images is crucial for the quality of fusion results. Although context adaptive (CA) injection models have been proposed in the framework of MRA, their adoption in CS schemes has been scarcely investigated so far. In this work a CA injection model already tested for MRA algorithms is evaluated also for CS schemes. Qualitative and quantitative results reported for IKONOS high spatial resolution data show that CA injection models are more efficient than global ones.
Year
DOI
Venue
2007
10.1007/978-3-540-77051-0_14
SAMT
Keywords
Field
DocType
pan image,spatial detail,fusion result,ikonos high spatial resolution,ms band,injection model,image fusion algorithm,multispectral image,context-sensitive pan-sharpening,mra algorithm,cs scheme,ca injection model,multiresolution analysis,multispectral images,image fusion
Sharpening,Computer vision,Image fusion,Computer science,Panchromatic film,Multispectral image,Multiresolution analysis,Artificial intelligence,Merge (version control),Image resolution
Conference
Volume
ISSN
ISBN
4816
0302-9743
3-540-77033-X
Citations 
PageRank 
References 
1
0.35
4
Authors
7
Name
Order
Citations
PageRank
Bruno Aiazzi127527.84
Luciano Alparone290180.27
Stefano Baronti355950.87
Andrea Garzelli457441.36
Franco Lotti5747.20
Filippo Nencini653130.47
Massimo Selva7877.92