M. Diani

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This paper deals with the problem of retrieving optically active parameters of the water from multispectral remotely sensed data. We analyse the neural networks approach applied to the estimation of chlorophyll concentration in coastal waters (Case II Waters) and discuss the use of two types of networks: the Radial Basis Function neural network and(More)
In this paper a new algorithm for striping noise reduction in hyperspectral images is proposed. Signal dependent striping noise is reduced by exploiting the high degree of spectral correlation of the useful signal in hyperspectral data. The algorithm does not require the human intervention nor introduces significant radiometric distortions on the useful(More)
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