M. Ronnier Luo

A study of digital camera colorimetric characterization based on polynomial modeling

The digital camera is a powerful tool to capture images for use in image processing and colour communication. However, the RGB signals generated by a digital camera are device-dependent, i.e. different digital cameras produce different RGB responses for the same scene. Furthermore, they are not colorimetric, i.e. the output RGB signals do not directly correspond to the device-independent tristimulus values based on the CIE standard colorimetric observer. One approach for deriving a colorimetric mapping between camera RGB signals and CIE tristimulus values uses polynomial modelling and is described here. The least-squares fitting technique was used to derive the coefficients of 3× n polynomial transfer matrices yielding a modelling accuracy typically averaging 1 Δ E units in CMC(1:1) when a 3× 11 matrix is used. Experiments were carried out to investigate the repeatability of the digitising system, characterisation performance when different polynomials were used, modelling accuracy when 8-bit and 12-bit RGB data were used for characterisation and the number of reference samples needed to achieve a reasonable degree of modelling accuracy. Choice of characterisation target and media and their effect on metamerism have been examined. It is demonstrated that a model is dependent upon both media and colorant and applying a model to other media/colorants can lead to serious eye-camera metamerism problems.

INVESTIGATION OF PARAMETRIC EFFECTS USING LARGE COLOUR DIFFERENCES

This experiment was carried out to investigate some viewing parameters affecting perceived colour differences. It was divided into eight phases. Each phase was conducted under a different set of experimental conditions including separations, neutral backgrounds, and psychophysical methods. Seventy-five wool sample pairs were prepared corresponding to five CIE colour centers. The mean colour difference was three CIELAB units. Each pair was assessed by a panel of 21 observers using both the gray scale and pair comparison psychophysical methods. The assessments were carried out using the three different backgrounds (white, mid-gray, and black) and a hairline gap between the samples. Assessments on the gray background were repeated using a large (3-inch) gap between the samples. It was found that the visual results obtained from both psychophysical methods gave very similar results. The parametric effect was small, i.e., the largest effect was only 14% between the white and gray background conditions. These visual data were also used to test four colour-difference formulae: CIELAB, CMC, BFD, and CIE94. The results showed that three advanced colour-difference formulae performed much better than CIELAB. There was a good agreement between the current results and those from earlier studies.

The LLAB (l:c) colour model

A new colour model, named LLAB(l:c) is derived. It includes two parts: the BFD chromatic adaptation transform derived by Lam and Rigg, and a modified CIELAB uniform colour space. The models performance was compared with the other spaces and models using the LUTCHI Colour Appearance Data Set. The results show that LLAB(l:c) model is capable of precisely quantifying the change of colour appearance under a wide range of viewing parameters such as light sources, surrounds/media, achromatic backgrounds, sizes of stimuli, and luminance levels. It had a similar performance as that of the Hunt colour appearance model. The LLAB(l:c) model was also tested using various colour difference datasets. The model gave a similar performance as the state-of-the-art colour difference formulae such as CMC, CIE94, and BFD. This performance is considered to be very satisfactory, and the model, therefore, should be considered for field trials in applications such as colour specification, colour difference evaluation, cross-image reproduction, gamut mapping, prediction of metamerism and colour constancy, and quantification of colour-rendering properties. The model does not give predictions for chroma (as distinct from colourfulness), or for brightness, and it does not include any rod response.

Calculating Medium and Image Gamut Boundaries for Gamut Mapping

The Segment Maxima Method for calculating gamut boundary descriptors of both colour reproduction media and colour images is introduced. Methods for determining the gamut boundary along a given line of mapping used by gamut mapping algorithms are then described, whereby these methods use the Gamut Boundary Descriptor obtained using the Segment Maxima Method. Throughout the article, the focus is both on colour reproduction media and colour images as well as on the suitability of the methods for use in gamut mapping.

A colour-difference formula for assessing large colour differences

An experiment was carried out to study large colour differences. Two-hundred-and-ninety-two wool pairs were prepared with an average difference of 12 CIELAB ΔE units. Visual assessments were conducted using gray scale and pair comparison psychophysical methods by a panel of 20 observers. The results from the two psychophysical methods were used to test colour-difference formulae and compare their differences. The gray scale results were also used to compare with the other large colour-difference data sets, i.e., BFB, OSA, and WW. The present results together with part of the other data sets were combined to form a single data set. A modified CIELAB colour-difference formula was developed having a structure similar to that of CIE94. It is named the GLAB colour-difference formula.

Factors affecting the psychophysical image quality evaluation of mobile phone displays: the case of transmissive liquid-crystal displays

Display manufacturers require new data and computational models that consider the effect of ambient illumination in order to develop higher-quality displays. In this study, typical variations of small-sized mobile LCDs that exist in the real world were first simulated using a device characterization technique. In addition, psychophysical attributes (e.g., naturalness, clearness, sharpness, contrast, colorfulness, and preference) affecting the image quality evaluation process were analyzed. Consequently, naturalness and clearness were found to be the most statistically significant psychophysical attributes for modeling image quality. As the ambient-illumination level was increased, the image quality was exponentially impaired and the contribution of clearness increased.

Notes on the application of the standardized residual sum of squares index for the assessment of intra- and inter-observer variability in color-difference experiments

The standardized residual sum of squares index was proposed to examine the significant merit of a given color-difference formula over another with respect to a given set of visual color-difference data [J. Opt. Soc. Am. A 24, 1823-1829, 2007]. This index can also be employed to determine intra- and inter-observer variability, although the full complexity of this variability cannot be described by just one number. Appropriate utilization of the standardized residual sum of squares index for the assessment of observer variability is described with a view to encourage its use in future color-difference research. The main goal of this paper is to demonstrate that setting the F parameters of the standardized residual sum of squares index to 1 results in a loss of essential properties of the index (for example, symmetry), and is therefore strongly discouraged.

Assessing total differences for effective samples having variations in color, coarseness, and glint

Effect coatings have the unique property of large change of appearance under different viewing conditions. This results in quality control problems of related products. In this letter, samples of metallic panels with effect coatings are visually assessed and measured. Based on experimental results, we propose formulae to predict precisely the total differences of effective samples in terms of variations in color, coarseness, and glint. Under diffused illumination, the total difference formula includes color difference and coarseness difference. Under directional illumination, the total difference formula includes color difference and glint difference.

A study of atmosphere perception of dynamic coloured light

A psychophysical experiment has been carried out to investigate the impact of dynamic lighting parameters on atmosphere perception. The experiment was conducted in a purpose-built LED lighting lab, where the lighting could be spatially and dynamically changed and colorimetric specifications controlled. The aim of this study was to investigate the impacts of speed, saturation and brightness of dynamic lighting on the perceived atmosphere, preference and suitability for certain spaces. Twenty native Chinese observers participated in the experiment, each assessing the environment under dynamic lighting conditions using 21 atmosphere terms. The results show significant gender differences on some scales such as safe, spatial, chilly, formal, preference and office-like. Factor analysis showed that the 21 scales can be grouped into three categories: tenseness, coziness and liveliness, and that a living room-like atmosphere evaluation is consistent with coziness. Dynamic lighting does have a significant influence on atmosphere perception. A more saturated LED light would lead to less tense, more cosy, more safe and more lively atmosphere perceptions. By increasing the speed, a more tense and less cosy atmosphere can be generated. Medium speed offers the most lively and preferred atmosphere. Brighter lighting will generate a less tense environment. More saturated colour and a slower speed will produce a more living room-like environment, but it seems that such dynamic lighting is not suitable for an office-like environment.

Evaluation of threshold color differences using printed samples

The performances of uniform color spaces and color-difference formulae for predicting threshold color differences were investigated based on visual assessments of 893 pairs of printed color patches under a D65 source. The average ΔE(ab,10)* of the pairs was 1.1 units. A threshold psychophysical experiment was repeated three times by a panel of 16 observers with normal color vision. The experimental data were used to evaluate nine color-difference formulae and uniform color spaces using the standardized residual sum of squares (STRESS) measure. The results indicated that all formulae and spaces performed very similarly to each other, and outperformed CIELAB for threshold color differences. The chromaticity-discrimination ellipses were used to compare with previous results from small color differences [Color Res. Appl. (2011), doi:10.1002/col.20689], and they agreed with each other, except for the purple color center.