2014
DOI: 10.1137/130928625
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Abstract: Pansharpening refers to the fusion process of inferring a high-resolution multispectral image from a high-resolution panchromatic image and a low-resolution multispectral one. In this paper we propose a new variational method for pansharpening which incorporates a nonlocal regularization term and two fidelity terms, one describing the relation between the panchromatic image and the highresolution spectral channels and the other one preserving the colors from the low-resolution modality. The nonlocal term is ba… Show more

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Cited by 72 publications
(39 citation statements)
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“…Further references about the nonlocal approach, targeted specifically towards the regularization of inverse problems in image processing, can be found e.g. in [24]- [31].…”
Section: A the Nonlocal Frameworkmentioning
confidence: 99%
“…Further references about the nonlocal approach, targeted specifically towards the regularization of inverse problems in image processing, can be found e.g. in [24]- [31].…”
Section: A the Nonlocal Frameworkmentioning
confidence: 99%
“…In this paper, we propose a new nonlocal variational model for the pansharpening of real satellite images. Compared to the previous work [20], no assumption on the co-registration of spectral data is made. Furthermore, a new constraint imposing the preservation of the radiometric ratio between the panchromatic and each spectral band is introduced, replacing the classical linearity assumption.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, P+XS functional incorporated an additional term according to which the panchromatic is a linear combination of the spectral components which are to be computed. Duran et al [20] proposed to keep the variational formulation introduced by Ballester et al [9] while incorporating nonlocal regularization that takes advantage of image self-similarities and leds to a significant reduction of color artifacts. In this setting, the panchromatic image is used to derive relationships among patches describing the geometry of the desired fused image.…”
Section: Introductionmentioning
confidence: 99%
“…In this setting, Palsson, Sveinsson, and Ulfarsson (2014) presented afterwards a simple explicit image formation model with Tikhonov and TV regularization. More recently, a new variational method that incorporates a non-local regularization term and two fidelity terms was introduced by Duran et al (2014). Although the above-mentioned methods are promising, there is still some room for further improvement.…”
Section: Introductionmentioning
confidence: 99%