Colorimetric tolerances of various digital image displays

Visual experiments on four displays (two LCD, one CRT and hardcopy) were conducted to determine colorimetric tolerances of images systematically altered via three different transfer curves. The curves used were: Sigmoidal compression in L*, linear reduction in C*, and additive rotations in hab. More than 30 observers judged the detectability of these alterations on three pictorial images for each display. Standard probit analysis was then used to determine the detection thresholds for the alterations. It was found that the detection thresholds on LCD\u27s were similar or lower than for the CRT\u27s in this type of experiment. Summarizing pixel-by-pixel image differences using the 90th percentile color difference in E*ab was shown to be more consistent than similar measures in E94 and a prototype E2000. It was also shown that using the 90th percentile difference was more consistent than the average pixel wise difference. Furthermore, SCIELAB pre-filtering was shown to have little to no effect on the results of this experiment since only global color-changes were applied and no spatial alterations were used

Colorimetric tolerances of digital images

An environment to derive colorimetric tolerances of images was established and an experiment using this new environment was performed. This environment allows for images to be digitally captured, colorimetrically manipulated, displayed, observed, and statistically evaluated. The visual experiment measured perceptibility and acceptability colorimetric tolerances for images using paired comparison techniques. Thirty-two observers judged six typical photographic scenes displayed on a high resolution color monitor. These scenes were manipulated using ten linear and nonlinear functions in the CIELAB dimensions of lightness, chroma, and hue angle. The tolerances were determined using probit analysis. It was found that scene content did not significantly affect the tolerances. The CIELAB, CMC, and MCSL color difference equations were shown to be inadequate for accurately modeling image tolerances. Finally, possible applications of this work are described

Evaluation of the press calibration methods by simulation

Press calibration is an approach to adjust the behavior of ink, paper, and press with the use of a CTP platemaking system to achieve a specified reference printing condition. Reference printing condition defines a common color space for color image data exchange between various output devices. The advantage of a reference printing condition is to improve color image quality and reduce cost and time. Corner points of the color gamut, TVI curves, and grey reproduction are the three significant elements in a reference printing condition, which make them essential in press calibration. There are usually two press runs in press calibration. The first press run (Run 1) is to adjust ink system of a press to achieve the color gamut conformance to the reference aims with linear plates. The second press run (Run 2) is to either adjust tonality or neutrality of the press with curved plates based on the Run 1 printing condition. Thus, the question is whether the two press calibration runs can meet the three requirements achieving full conformance according to the reference aims? This research assessed two cases starting with two real Run 1 printing conditions. In the both cases, ISO Type 1 paper was used and the color gamut was in conformance to the reference CGATS TR006 printing condition. Run 2 was a simulated calibration press run with the adjustment of either tonality or neutrality of the press. The use of A-to-B tag and B-to-A tag of the Run 1 ICC profile with absolute colorimetric rendering intent was the essential idea to simulate a calibrated Run 2 printing condition. The advantage is that no printing drafts would occur in the simulation approach, which guarantees repeatability from Run 1 to Run 2. The calibration results were verified to be in conformance first before other assessments. In other words, TVI curves of the TVI-based calibrated results were verified to be in conformance first before grey reproduction conformance was assessed; and grey reproduction of G7-based calibration results was verified to be in conformance first before TVI curves\u27 conformance was assessed. The research results show that (1) if deviations of TVI curves and grey reproduction in Run 1 printing conditions are close to the reference aims, either of the two calibration methods can achieve full conformance; and (2) if discrepancies of TVI curves and grey reproduction conformance in Run 1 printing conditions are far from the reference aims, a third requirement may not be in conformance unless adjustments will be iterated within specified tolerances

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Test Targets 6.0: A Collaborative effort exploring the use of scientific methods for color imaging and process control

Test Targets is a collection of scholarly papers contributed by faculty, students, and alumni of Rochester Institute of Technology. We realize the importance of having faculty set examples as authors for students to follow. We have a three-course sequence over a time span of a year to prepare students to publish their first articles when completing Tone and Color Analysis, Printing Process Control, and Advanced Color Management. In this instance, Test Targets 6.0 is a part of the course content in the Advanced Color Management course

Preferences and tolerances in color image reproduction

Observer preferences in the color reproduction of pictorial images have been a topic of debate for many years. Through a series of three psychophysical experiments we are trying to better understand the differences and trends in observer preferences for pictorial images, determine if cultural biases on preference exist, and finally generate a set of preferred color reproduced images for future experimentation and evaluation. The first experiment was a survey of observers rating the importance of commonly used image characteristics terms in correlation to color image quality. The data collected demonstrated that observer preferences remain relatively constant while judging color attributes between different media and for various image content. Experiment I also aided in the decision to utilize five dimensions of manipulation to generate preferred color reproductions, for Experiments II and in. The dimensions were, lightness (gamma adjustment to L*), contrast (sigmoid adjustment to L*), chroma (multiplicative factor on Cab* at a given hab), hue rotation, and color balance (additive adjustments to a* and b*). The second experiment was a rank order of image preference conducted at several research facilities around the world. The results yielded that statistical difference between peak preferences of image quality between cultures may exist but that the cultural difference is most likely not of practical significance for most applications. Furthermore, the shape of the preference curves across cultures is very similar so any cultural bias present is small. The final experiment was an adjustment experiment, in which observers were asked to generate the most preferred image possible. The observer variability (inter-observers) and repeatability (intra-observer) in generating preferred images were analyzed. The analysis of Experiment HI yielded that the intra-observer repeatability of an observer is about half of the variation between observers. Furthermore the analysis demonstrated that preferences on images with faces have a much tighter range of preference in comparison to images without faces. Finally, a cross analysis of Experiment II and HI was completed by the generation of preferred image sets from the results of the two experiments. The resultant images proved to be a good visualization of the range of variability in making preferred images from the color dimensions provided, and also visually demonstrated that the two techniques, (making one color adjustment at a time verses compounding color adjustments) of generating preferred images result in similar solutions

Measuring Perceptual Color Differences of Smartphone Photographs

Measuring perceptual color differences (CDs) is of great importance in modern smartphone photography. Despite the long history, most CD measures have been constrained by psychophysical data of homogeneous color patches or a limited number of simplistic natural photographic images. It is thus questionable whether existing CD measures generalize in the age of smartphone photography characterized by greater content complexities and learning-based image signal processors. In this paper, we put together so far the largest image dataset for perceptual CD assessment, in which the photographic images are 1) captured by six flagship smartphones, 2) altered by Photoshop, 3) post-processed by built-in filters of the smartphones, and 4) reproduced with incorrect color profiles. We then conduct a large-scale psychophysical experiment to gather perceptual CDs of 30,000 image pairs in a carefully controlled laboratory environment. Based on the newly established dataset, we make one of the first attempts to construct an end-to-end learnable CD formula based on a lightweight neural network, as a generalization of several previous metrics. Extensive experiments demonstrate that the optimized formula outperforms 33 existing CD measures by a large margin, offers reasonable local CD maps without the use of dense supervision, generalizes well to homogeneous color patch data, and empirically behaves as a proper metric in the mathematical sense. Our dataset and code are publicly available at https://github.com/hellooks/CDNet.Comment: 10 figures, 8 tables, 14 page

Test Targets 7.0: A Collaborative effort exploring the use of scientific methods for color imaging and process control

Test Targets is a culmination of teaching and learning that reflects quality and analytic aspects of printing systems and their optimization. The creation of the Test Targets publication is a total experience that reflects the innovation, problem solving, and teamwork of the diverse team of faculty, staff, students, and professionals responsible for its contents and production

Effects of texture on color difference evaluation of surface color

The parametric effects of texture on supratheshold color tolerance thresholds were investigated in two psychophysical experiments using simulated textures presented on a CRT. Textured images were created from scanned photographs of physical texture samples with semi-random textured pattern. Differences in appearance were created by varying the illumination geometry during the image capture stage. Two conditions were simulated: diffuse illumination of a standard light booth and directional lighting which accentuates texture relief. In the first experiment observers matched average perceived lightness of grayscale textured images by adjusting the lightness of a uniform gray field. Images varied in their average L*. The results showed that, on average, there was no statistically significant difference between the observer match and the average L of the image. The only exception was found for darker images of coarse texture. In the second experiment, an array of color images was created from three texture patterns: one simulating diffuse lighting conditions and two simulating directional illumination. The CTELAB coordinates of the images were centered around the five CEE color centers recommended for color tolerance research. Color differences were varied in the lightness, chroma, and hue dimensions. Color tolerance thresholds were measured in each dimension for each texture type and uniform patches. An adaptive psychophysical technique, QUEST, was utilized to determine color tolerances in a greater than/less than task using test pairs in comparison to a fixed anchor pair of 1 unit AE*94. The results indicated that the presence of texture increases tolerance thresholds for hue irrespective of the texture pattern. The chroma dimension remained unaffected. Less conclusive results were found for lightness dimension with a strong trend toward increased tolerance thresholds for textured stimuli. When the different textures were compared, it was found that the L* thresholds were significantly higher for the images simulating directional lighting compared to the images of diffusely illuminated surface. No differences in tolerances for chroma and hue were found in that case

Data-efficient methods applied to general spectral image capture

Commercialization of spectral imaging for color reproduction will require low bandwidth but highly accurate spectral image acquisition systems. Self-adapting systems are proposed as potential solutions. Such systems perform spectral content analysis on an encountered scene, reacting to the analysis by configuring efficient high quality spectral reconstruction. An experiment is reported comparing scene-derived spectral estimation transforms to static global transforms in multi-channel imaging simulations. For noisefree simulations, the adaptive approach showed clear benefit in terms of colorimetric and spectral statistics. When noise was added, the adaptive method continued to be superior in terms of spectral evaluations, but colorimetric degradation for the adaptive approach exceeded that of the static. This provided additional evidence that spectral reconstruction methods should reference psychometrics as an integral part of spectral error management