TY - GEN
T1 - Super resolution of multispectral images using ℓ1 image models and interband correlations
AU - Vega, Miguel
AU - Mateos, Javier
AU - Molina, Rafael
AU - Katsaggelos, Aggelos K
PY - 2009/12/1
Y1 - 2009/12/1
N2 - In this paper we propose a novel super-resolution based algorithm for the pansharpening of multispectral images. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images; that is, imposes smoothness within each band by means of the energy associated to the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation between the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and its quality is assessed both qualitatively and quantitatively.
AB - In this paper we propose a novel super-resolution based algorithm for the pansharpening of multispectral images. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images; that is, imposes smoothness within each band by means of the energy associated to the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation between the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and its quality is assessed both qualitatively and quantitatively.
UR - http://www.scopus.com/inward/record.url?scp=77950960267&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950960267&partnerID=8YFLogxK
U2 - 10.1109/MLSP.2009.5306217
DO - 10.1109/MLSP.2009.5306217
M3 - Conference contribution
AN - SCOPUS:77950960267
SN - 9781424449484
T3 - Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009
BT - Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009
T2 - Machine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009
Y2 - 2 September 2009 through 4 September 2009
ER -