Spatio-Spectral Gamut Mapping and Separation

Spectral printing aims to achieve an illuminant-invariant match between the original and the reproduction. Due to limited printer spectral gamuts, an errorless spectral reproduction is mostly impossible, and spectral gamut mapping is required to reduce perceptual errors. The recently proposed paramermismatch-based spectral gamut mapping (PMSGM) strategy minimizes such errors. However, due to its pixel-wise processing, it may result in severely different tonal values for spectrally similar adjacent pixels, causing unwanted edges (banding) in the final printout. While the addition of some noise to the a* and b* channels of the colorimetric (e.g., CIELAB) image—rendered for the first illuminant—prior to gamut mapping solves the banding problem, it adversely increases the image graininess. In this article, the authors combine the PMSGM strategy with subsequent spectral separation, considering the spatial neighborhood within the tonal-value space and the illuminant-dependent perceptual spaces to directly compute tonal values. Their results show significant improvements to the PMSGM method in terms of avoiding banding artifacts. c © 2015 Society for Imaging Science and Technology. [DOI: 10.2352/J.ImagingSci.Technol.2015.59.4.040402] INTRODUCTION The quality of hardcopy reproduction is often adversely affected by limitations of printing systems, particularly the colorimetric gamut. It is defined by all colors printable by a device considering specific media, inks and viewing conditions, i.e., an illuminant and observer. Since conventional printing systems utilize four colorants (CMYK), the colorimetric gamut is usually restricted in the secondary colors (red, green and blue). Nowadays, there are multichannel printers using more than four colorants (e.g., CMYKRGB) in order to expand the printer gamut. Although by utilizing these kinds of printing systems, the reproduction of more colors is possible, out-of-gamut colors must still be mapped into the printer gamut by employing colorimetric gamut mapping algorithms (GMAs).1 These methods commonly have the aim ofminimizing the perceived difference between the original input image and the final print for one considered illuminant. A byproduct of such multichannel printers is a high colorimetric redundancy, i.e., that different colorant com-