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Pansharpening is a technique that fuses a low resolution multispectral image and a high resolution panchromatic image, to obtain a multispectral image with the spatial resolution and quality of the panchromatic image while preserving spectral information of the multispectral image. In this paper, we present a new pansharpening method based on super-resolution and contourlet transform. The experimental...
This paper is devoted to the combination of image priors in Super Resolution (SR) image reconstruction. Taking into account that each combination of a given observation model and a prior model produces a different posterior distribution of the underlying High Resolution (HR) image, the use of variational posterior distribution approximation on each posterior will produce as many posterior approximations...
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 lscr1 norm of vertical and horizontal first order differences...
This paper deals with the problem of high-resolution (HR) image reconstruction, from a set of degraded, under-sampled, shifted and rotated images, under the Bayesian paradigm, utilizing a variational approximation. Bayesian methods rely on image models that encapsulate prior image knowledge and avoid the ill-posedness of the image restoration problems. In this paper a new prior based on the lscr1...
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