TY - GEN
T1 - Pansharpening via sparsity optimization using overcomplete transforms
AU - Palsson, Frosti
AU - Sveinsson, Johannes R.
AU - Ulfarsson, Magnus O.
AU - Benediktsson, Jon A.
PY - 2013
Y1 - 2013
N2 - In this paper we consider pansharpening of multispectral satellite imagery based on solving an under-determined inverse problem regularized by the ℓ1-norm of the coefficients of overcomplete multi-scale transforms which all are tight-frame systems. There are two main approaches in sparsity promoting ℓ1-norm regularization, the analysis and the synthesis approach. We perform a number of experiments using two real and well known datasets where the focus is the comparison of the two approaches. One dataset includes a high resolution reference image while the other needs to be degraded prior to pansharpening in order to use the original multispectral image as the reference. Experiments are performed for a range of values for the regularization parameter, where each resulting pansharpened image is evaluated using three quality metrics. The behavior of those metrics as a function of the regularization parameter is compared for the analysis and synthesis formulations and it is shown that analysis gives better results.
AB - In this paper we consider pansharpening of multispectral satellite imagery based on solving an under-determined inverse problem regularized by the ℓ1-norm of the coefficients of overcomplete multi-scale transforms which all are tight-frame systems. There are two main approaches in sparsity promoting ℓ1-norm regularization, the analysis and the synthesis approach. We perform a number of experiments using two real and well known datasets where the focus is the comparison of the two approaches. One dataset includes a high resolution reference image while the other needs to be degraded prior to pansharpening in order to use the original multispectral image as the reference. Experiments are performed for a range of values for the regularization parameter, where each resulting pansharpened image is evaluated using three quality metrics. The behavior of those metrics as a function of the regularization parameter is compared for the analysis and synthesis formulations and it is shown that analysis gives better results.
UR - http://www.scopus.com/inward/record.url?scp=84894256386&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2013.6721294
DO - 10.1109/IGARSS.2013.6721294
M3 - Conference contribution
AN - SCOPUS:84894256386
SN - 9781479911141
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 856
EP - 859
BT - 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
T2 - 2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Y2 - 21 July 2013 through 26 July 2013
ER -