Model-based approaches to pansharpening still constitute a class of widely employed methods, thanks to their straightforward applicability to many problems, dispensing the user from time-consuming training phases. The injection scheme based on an accurate estimation (exploiting regression) of the relationship between the details contained in the panchromatic (PAN) image and those required for the enhancement of the multispectral (MS) image represents the most updated approach to this problem, being characterized by both theoretical and practical optimality. We elaborated on this scheme by designing a procedure for estimating the key parameters required for the optimal setting of such a regression-based approach. We tested this approach on several datasets acquired by the WorldView satellites comparing the proposed approach with a benchmark consisting of some state-of-the-art pansharpening methods.

An Optimization Procedure for Robust Regression-Based Pansharpening

Carpentiero, M;Vivone, G
;
Restaino, R;Addesso, P;
2022-01-01

Abstract

Model-based approaches to pansharpening still constitute a class of widely employed methods, thanks to their straightforward applicability to many problems, dispensing the user from time-consuming training phases. The injection scheme based on an accurate estimation (exploiting regression) of the relationship between the details contained in the panchromatic (PAN) image and those required for the enhancement of the multispectral (MS) image represents the most updated approach to this problem, being characterized by both theoretical and practical optimality. We elaborated on this scheme by designing a procedure for estimating the key parameters required for the optimal setting of such a regression-based approach. We tested this approach on several datasets acquired by the WorldView satellites comparing the proposed approach with a benchmark consisting of some state-of-the-art pansharpening methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4815382
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