
doi: 10.1002/col.20625
handle: 11379/459051
AbstractIn this work, several near‐lossless compression methods for spectral images have been analyzed and compared. These methods are based both on the principal component analysis (PCA) and on the choice of a minimum number of spectral points, selected following different criteria. The analysis, initially carried out on 14 National Physical Laboratory tiles of certified colour, has been extended to some spectral images of paintings taken at the National Gallery of Parma (Italy). The comparison of the results with those obtained by applying the PCA analysis shows that the best method indicated as “method of a few significant points” allows reducing the spectral image size of a factor of 10 without loss of spectral and colour information. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010
Spectral images, Lossless spectral compression, color difference, root-mean-square error
Spectral images, Lossless spectral compression, color difference, root-mean-square error
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