Macro-uniformity refers to the subjective impression of overall uniformity in the print sample. By the efforts of INCITS
W1.1 team, macro-uniformity is categorized into five types of attributes: banding, streaks, mottle, gradients, and moiré
patterns, and the ruler samples are generated with perceptual scales. W1.1 macro-uniformity ruler is useful for judging
the levels of print defect, but it is not an easy task to reproduce the samples having the same perceptual scales at different
times in different places. An objective quantification method is more helpful and convenient for developers to analyze
print quality and design printing system components.
In this paper, we propose a method for measuring perceived macro-uniformity for a given print using a flat-bed scanner.
First, banding, 2D noise, and gradients are separately measured, and they are converted to the perceptual scales based on
subjective results of each attribute. The correlation coefficients between the measured values of the attributes and the
perceptual scales are 0.92, 0.97, and 0.86, respectively. Another subjective test is performed to find the relationship
between the overall macro-uniformity and the three attributes. The weighting factors are obtained by the experimental
result, and the final macro-uniformity grade is determined by the weighted sums of each attribute.
The techniques of one-dimensional projection in the spatial domain and contrast sensitivity function (CSF) are generally
used to measure banding. Due to the complex printing process of laser printers, hardcopy prints contain other 2D nonuniformities
such as graininess and mottle besides banding. The method of 1D projection is useful for extracting banding,
but it induces the confounding effect of graininess or mottle on the measurement of perceived banding. The appearance
of banding in laser printers is more similar to the sum of various rectangular signals having different amplitudes and
frequencies. However, in many cases banding is modeled as a simple sinusoidal signal and the CSF is frequently applied.
In this paper, we propose new measurement method of banding well correlated with human perception. Two kinds of
spatial features give a good performance to banding measurement. First the correlation factor between two adjacent 1D
signals is considered to obtain banding power which reduces the confounding effect of graininess and mottle. Secondly,
a spatial smoothing filter is designed and applied to reduce the less perceptible low frequency components instead of
using the CSF. By using moving window and subtracting the local mean values, the imperceptible low frequency
components are removed while the perceptible low frequency components like the sharp edge of rectangular waves are
preserved. To validate the proposed method, psychophysical tests are performed. The results show that the correlations
between the proposed method and the perceived scales are 0.96, 0.90, and 0.95 for black, cyan, and magenta,
Graininess and mottle described by ISO 13660 standard are two image quality attributes which are widely used to
evaluate area uniformity in digital prints. In an engineering aspect, it is convenient to classify and analyze high frequency
noise and low frequency noise separately. However, it is continuously reported in previous literature that the ISO
methods do not properly correlate with our perception. Since area quality is evaluated by observing all the characteristics
with a wide range of spectral frequencies in a printed page, it is almost impossible to differentiate between graininess and
mottle separately in our percept.
In this paper, we characterize '2D noise' print defect based on psychophysical experiments which appear as two
dimensional aperiodic fluctuations in digital prints. For each channel of cyan, magenta, and black, our approach is to use
two steps of hybrid filtering to remove invisible image components in the printed area. '2D noise' is computed as the
weighted sum of the graininess and mottle, which two weighting factors are determined by subjective evaluation
experiment. By conducting psychophysical validation experiments, the strong correlation is obtained between the
proposed metric and the perceived scales. The correlation coefficients r2 are 0.90, 0.86, and 0.78 for cyan, magenta and