Israa Amro

Abstract—Pansharpening is a technique that fuses the informa-tion of a low resolution multispectral image and a high resolution panchromatic image, usually remote sensing images, to produce a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets and contourlet based algorithms. Recently, the shearlet transform, has been proposed. This transform combines the advantages of the wavelets and contourlet transform, with a more efficient directional informa-tion representation. In this paper we propose a new shearlet based pansharpening algorithm that generalizes a number of pansharpening approaches and compare it with contourlet based and shearlet based methods. The performance of the proposed shearlet based method is assessed numerically and visually for synthetic and SPOT images. Index Terms—Pansharpening, Remote sensing, shearlet trans-form, Bayesian Inference.

This paper solves the problem of parameter estimation for the general contourlet pansharpening method using Bayesian inference. In the general contourlet panshapening method, a set of parameters that control the contribution of each band of the multispectral image, the panchromatic image and the prior knowledge on the image need to be set. The proposed method takes into account the relationship between contourlet coefficients to incorporate prior knowledge on the unknown parameters in the form of hyperprior distributions. This method is able to estimate all the unknown parameters together with the high resolution multispectral image in a fully automatic way. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image. 1.

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 contourlet transform and Bayesian inference that generalizes the classical contourlet based algorithms. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image. 1.

In this paper, we consider the problem of parameter estimation on the super resolution and Bayesian methodology for pansharpening using contourlet transform. The used methodology is able to incorporate prior knowledge on the expected characteristics of the multispectral images, include information on the unknown parameters in the form of hyperprior distributions and estimate the unknown parameters together with the high resolution multispectral image. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image. Index Terms — pansharpening, super-resolution, contourlets, multispectral image, remote sensing, parameter estimation

This paper solves the problem of parameter estimation for the general contourlet pansharpening method using Bayesian inference. In the general contourlet panshapening method, a set of parameters that control the contribution of each band of the multispectral image, the panchromatic image and the prior knowledge on the image need to be set. The proposed method takes into account the relationship between contourlet coefficients to incorporate prior knowledge on the unknown parameters in the form of hyperprior distributions. This method is able to estimate all the unknown parameters together with the high resolution multispectral image in a fully automatic way. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image.

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There exist a number of satellites on different earth observation platforms, which provide multispectral images together with a panchromatic image, that is, an image containing reflectance data representative of a wide range of bands and wavelengths. Pansharpening is a pixel-level fusion technique used to increase the spatial resolution of the multispectral image while simultaneously preserving its spectral information. In this paper, we provide a review of the pan-sharpening methods proposed in the literature giving a clear classification of them and a description of their main characteristics. Finally, we analyze how the quality of the pansharpened images can be assessed both visually and quantitatively and examine the different quality measures proposed for that purpose.