In September 2000, INCITS W1 (the U.S. representative of ISO/IEC JTC1/SC28, the standardization committee for office equipment) was chartered to develop an appearance-based image quality standard.(1),(2) The resulting W1.1 project is based on a proposal(4) that perceived image quality can be described by a small set of broad-based attributes. There are currently five ad hoc teams, each working towards the development of standards for evaluation of perceptual image quality of color printers for one or more of these image quality attributes. This paper summarizes the work in progress of the teams addressing the attributes of Macro-Uniformity, Color Rendition, Text and Line Quality and Micro-Uniformity.
The color rendition ad hoc team of INCITS W1.1 is working to address issues related to color and tone reproduction for printed output and its perceptual impact on color image quality. The scope of the work includes accuracy of specified colors with an emphasis on memory colors, color gamut, and the effective use of tone levels, including issues related to contouring. The team has identified three sub-attributes of color rendition: 1) color quantization, defined as the ability to merge colors where needed; 2) color scale, defined as the ability to distinguish color where needed; and 3) color fidelity, defined as a balance of colorimetric accuracy, in cases where a reference exists, and pleasing overall color appearance. Visual definitions and descriptions of how these sub-attributes are perceived have been developed. The team is presently working to define measurement methods for the sub-attributes, with the focus in 2004 being on color fidelity. This presentation will review the definitions and appearance of the proposed sub-attributes and the progress toward developing test targets and associated measurement methods to quantify the color quantization sub-attribute. The remainder of the discussion will focus on the recent progress made in developing measurement methods for the color fidelity sub-attribute.
This paper describes a regression model for predicting customer preference from objective image quality metrics for black and white printers, copiers and multifunction systems. In order to quantify customer preference for monochrome images the quantitative preference system was previously developed. Using this system, a preference survey with five different customer-type documents was used to obtain the preference data. Objective image quality metrics were obtained from a scanner-based measurement system. Using this regression model, typically 80% or more of the variation of the overall preference can be explained by six objective image quality metrics: Relative TRC Error; Mottle; Visual Noise; Visual Structure; Streaks and Bands; and Relative Dynamic Range Reduction. The results also provide the relative significance of these attributes for the different kinds of customer images.