- Color Image Quality Metric S-CIELAB and...

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Color Image Quality Metric S-CIELAB and Its Application on Halftone Texture Visibility Xuemei Zhang Department of Psychology Stanford University Stanford, CA 94305 [email protected] D. Amnon Silverstein, Joyce E. Farrell Hewlett Packard Laboratories 1501 Page Mill Road Palo Alto, CA 94304 [email protected], [email protected] Brian A. Wandell Department of Psychology Stanford University Stanford, CA 94305 [email protected] Abstract We describe experimental tests of a spatial extension to the CIELAB color metric for measuring color reproduction errors of digital images. The standard CIELAB Eme tr ic is suitable for use on large uniform color targets, but not on images, because color sensitivity changes as a function of spatial pattern. The S-CIELAB extension includes a spatial processing step, prior to the CIELAB E calculation,so that the results correspond better to color difference perception by the human eye. The S-CIELAB metric was used to predict texture visibil- ity of printed halftone patterns. The results correlate with perceptual data better than standard CIELAB and point the way to various improvements. 1. Introduction In digital color imaging applications, it is often necessary to evaluate the visibility of color reproduction errors. The decision to proceed or not with a hardware modification can depend on the predicted color reproduction error caused by the hardware change. To measure perceptual color differences between two color images, we must account for several aspects of human visual sensitivity. First, human sensitivity to color differ- ences is not uniform in linear color spaces such as the CIE XYZ color space [9]. Distance between two colors in a linear color space does not correspond to perceptual differ- ences between them. Second, sensitivity to color differences depends on the color of the background or adaptation state of the eye, which can be changed by ambient illumination [1, 17, 8, 15]. Third, sensitivity to color differences also depends on spatial pattern [2, 10, 11, 12]. These are all significant visual effects. There has been theoretical work on incorporating each of these factors into modern color metrics. The CIELAB transformation incorporates the fact that perceptual differences among colors are not uniform in a linear color space. This metric is widely used in industry to measure color reproduction errors [6, 7, 3]. The CIELAB metrictransforms colors to arepresentation which is approx- imately perceptually uniform in the sense that Euclidean distances between different colors in this space correspond roughly to perceived color differences. The CIELAB trans- formationis based on data from color matching and discrim- ination experiments using large uniform test fields under fixed adaptation condition. While imperfect, it works rea- sonably well in applicationsinvolvinglarge uniform patches
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