Exploring s-CIELAB as a scanner metric for print uniformity

The s-CIELAB color difference metric combines the standard CIELAB metric for perceived color difference with spatial contrast sensitivity filtering. When studying the performance of digital image processing algorithms, maps of spatial color difference between 'before' and 'after' images are a measure of perceived image difference. A general image quality metric can be obtained by modeling the perceived difference from an ideal image. This paper explores the s-CIELAB concept for evaluating the quality of digital prints. Prints present the challenge that the 'ideal print' which should serve as the reference when calculating the delta E* error map is unknown, and thus be estimated from the scanned print. A reasonable estimate of what the ideal print 'should have been' is possible at least for images of known content such as flat fields or continuous wedges, where the error map can be calculated against a global or local mean. While such maps showing the perceived error at each pixel are extremely useful when analyzing print defects, it is desirable to statistically reduce them to a more manageable dataset. Examples of digital print uniformity are given, and the effect of specific print defects on the s-CIELAB delta E* metric are discussed.