Ink-saving strategies for CMYK printers have evolved from their earlier stages where the 'draft' print mode was
the main option available to control ink usage. The savings were achieved by printing alternate dots in an image
at the expense of reducing print quality considerably. Nowadays, customers are not only unwilling to compromise
quality but have higher expectations regarding both visual print quality and ink reduction solutions. Therefore,
the need for more intricate ink-saving solutions with lower impact on print quality is evident. Printing-related
factors such as the way the printer places the dots on the paper and the ink-substrate interaction play important
and complex roles in the characterization and modeling of the printing process that make the ink reduction
topic a challenging problem. In our study, we are interested in benchmarking ink-saving algorithms to find
the connections between different ink reduction levels of a given ink-saving method and a set of print quality
attributes. This study is mostly related to CMYK printers that use dispersed dot halftoning algorithms. The
results of our efforts to develop such an evaluation scheme are presented in this paper.
Common ink-saving techniques usually restrict the ink consumption when printing a document by replacing
a percentage of cyan, magenta, and yellow, by black ink. Even though such methods achieve a considerable
reduction in the amount of ink used in a page, the visual quality of the print is affected and unpleasing effects
in pastels and skin tones are observed. On the other hand, the quality of the print is not only affected by
the ink-saving algorithm, but also by the way the color halftoning algorithm arranges the dots in the print.
Therefore, the relationship between the contents of the document to be printed and the printing process needs to
be addressed by the ink-saving strategy. A color direct binary search halftoning method that strives to minimize
both the ink usage and the perceived error between the continuous-tone color image and the color halftone image
is proposed. Our goals are to estimate the effects of the ink-saving module of a printing workflow in individual
regions of the document, and to determine the dot arrangement and ink combination that consumes the least
amount of ink while preserving printing quality.
We present a novel framework for automatically determining whether or not to apply black point compensation
(BPC) in image reproduction. Visually salient objects have a larger influence on determining image quality
than the number of dark pixels in an image, and thus should drive the use of BPC. We propose a simple and
efficient algorithmic implementation to determine when to apply BPC based on low-level saliency estimation.
We evaluate our algorithm with a psychophysical experiment on an image data set printed with or without BPC
on a Canon printer. We find that our algorithm is correctly able to predict the observers' preferences in all cases
when the saliency maps are unambiguous and accurate.
Image quality metrics have become more and more popular in the image processing community. However, so far, no one
has been able to define an image quality metric well correlated with the percept for overall image quality. One of the causes
is that image quality is multi-dimensional and complex. One approach to bridge the gap between perceived and calculated
image quality is to reduce the complexity of image quality, by breaking the overall quality into a set of quality attributes. In
our research we have presented a set of quality attributes built on existing attributes from the literature. The six proposed
quality attributes are: sharpness, color, lightness, artifacts, contrast, and physical. This set keeps the dimensionality to a
minimum. An experiment validated the quality attributes as suitable for image quality evaluation.
The process of applying image quality metrics to printed images is not straightforward, because image quality metrics
require a digital input. A framework has been developed for this process, which includes scanning the print to get a digital
copy, image registration, and the application of image quality metrics. With quality attributes for the evaluation of image
quality and a framework for applying image quality metrics, a selection of suitable image quality metrics for the different
quality attributes has been carried out. Each of the quality attributes has been investigated, and an experimental analysis
carried out to find the most suitable image quality metrics for the given quality attributes. For the sharpness attributes
the Structural SIMilarity index (SSIM) by Wang et al. (2004) is the the most suitable, and for the other attributes further
evaluation is required.
Increased interest in color management has resulted in more options for the user to choose between for their color
management needs. We propose an evaluation process that uses metrics to assess the quality of ICC profiles,
specifically for the perceptual rendering intent. The primary objective of the perceptual rendering intent, unlike
the media-relative intent, is a preferred reproduction rather than an exact match. Profile vendors commonly
quote a CIE ΔE*ab color difference to define the quality of a profile. With the perceptual rendering intent, this
may or may not correlate to the preferred reproduction.
For this work we compiled a comprehensive list of quality aspects, used to evaluate the perceptual rendering
intent of an ICC printer profile. The aspects are used as tools to individually judge the different qualities that
define the overall strength of profiles. The proposed workflow uses metrics to assess each aspect and delivers a
relative comparison between different printer profile options. The aim of the research is to improve the current
methods used to evaluate a printer profile, while reducing the amount of time required.
The capacity of a printing system to accurately reproduce details has an impact on the quality of printed images. The ability of a system to reproduce details is captured in its modulation transfer function (MTF). In the first part of this work, we compare three existing methods to measure the MTF of a printing system. After a thorough investigation, we select the method from Jang and Allebach and propose to modify it. We demonstrate that our proposed modification improves the measurement precision and the simplicity of implementation. Then we discuss the advantages and drawbacks of the different methods depending on the intended usage of the MTF and why Jang and Allebach's method best matches our needs. In the second part, we propose to improve the quality of printed images by compensating for the MTF of the printing system. The MTF is adaptively compensated in the Fourier domain, depending both on frequency and local mean values. Results of a category judgment experiment show significant improvement as the printed MTF-compensated images obtain the best scores.
The evaluation of perceived image quality in color prints is a complex task due to its subjectivity and dimensionality. The perceived quality of an image is influenced by a number of different quality attributes. It is difficult and complicated to evaluate the influence of all attributes on overall image quality, and their influence on other attributes. Because of this difficulty, the most important attributes of a color image should be identified to achieve a more efficient and manageable evaluation of the image's quality. Based on a survey of the existing literature and a psychophysical experiment, we identify and categorize existing image quality attributes to propose a refined selection of meaningful ones for the evaluation of color prints.
In this paper we compare three existing methods to measure the Modulation Transfer Function (MTF) of a
printing system. Although all three methods use very distinct approaches, the MTF values computed for two of
these methods strongly agree, lending credibility to these methods. Additionally, we propose an improvement to
one of these two methods, initially proposed by Jang & Allebach. We demonstrate that our proposed modification
improves the measurement precision and simplicity of implementation. Finally we discuss the pros and cons of
the methods depending on the intended usage of the MTF.
Premilary experiments have shown that the quality of printed images depends on the capacity of the printing
system to accurately reproduce details.<sup>1</sup> We propose to improve the quality of printed images by compensating
for the Modulation Transfer Function (MTF) of the printing system. The MTF of the printing system is
measured using the method proposed by Jang and Allebach,<sup>2</sup> in which test pages consisting of series of patches
with different 1D sinusoidal modulations (modified to improve the accuracy of the results<sup>3</sup>) are printed, scanned
and analyzed. Then the MTF is adaptively compensated in the Fourier domain, depending both on frequency
and local mean values. Results of a category judgment experiment show significant improvement as the printed
MTF compensated images obtain the best scores.
We explore two recent methods for measuring the Modeling Transfer Function of a printing system<sup>12</sup>. We
investigate the dependency on the amplitude when using the sinusoidal patches of the method proposed in<sup>1</sup> and
show that for too small amplitudes the measurement of the MTF is not trustworthy. For the method proposed
in<sup>2</sup> we discuss the underlying theory and in particular the use of a significance test for a statistical analysis.
Finally we compare both methods with respect our application - the processing and printing of photographic