Pansharpening via sparsity optimization using overcomplete transforms
- Resource Type
- Conference
- Authors
- Palsson, Frosti; Sveinsson, Johannes R.; Ulfarsson, Magnus O.; Benediktsson, Jon A.
- Source
- 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International. :856-859 Jul, 2013
- Subject
- Fields, Waves and Electromagnetics
Measurement
Wavelet analysis
Wavelet transforms
Spatial resolution
Analytical models
- Language
- ISSN
- 2153-6996
2153-7003
In this paper we consider pansharpening of multispectral satellite imagery based on solving an under-determined inverse problem regularized by the ℓ 1 -norm of the coefficients of overcomplete multi-scale transforms which all are tight-frame systems. There are two main approaches in sparsity promoting ℓ 1 -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.