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2010
IEEE

Characterization of signal perturbation using voting based curve fitting for multispectral images

8 years 11 months ago
Characterization of signal perturbation using voting based curve fitting for multispectral images
Signal degradation impacts the final quality of images acquired using remote sensing radiometer. The effectiveness of a restoration algorithm strongly depends on two main factors: an accurate model of the disturbs introduced by the acquisition device and adaptation of the filtering method to image content. In this paper we target the first factor, by providing a solution for characterizing multispectral image signal degradation. A framework for estimating signal disturbs from heterogeneous sets of multispectral images is presented jointly with a voting-based technique for determining the best coefficients of the fitting equation. Tests conducted on multispectral images confirm the effectiveness of the proposed approach.
Sebastiano Battiato, Giovanni Puglisi, Rosetta Riz
Added 03 Mar 2011
Updated 07 Apr 2013
Type Journal
Year 2010
Where ICIP
Authors Sebastiano Battiato, Giovanni Puglisi, Rosetta Rizzo
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