Multispectral images fusion by a joint multidirectional and multiresolution representation
International Journal of Remote Sensing
L1 prior majorization in Bayesian image restoration
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
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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, it imposes smoothness within each band by means of the energy associated with the 驴1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation among the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and the quality of the results assessed both qualitatively and quantitatively.