Optimized principal component analysis for camera spectral sensitivity estimation.

This paper describes the use of a weighted principal component analysis (PCA) method for camera spectral sensitivity estimation. A comprehensive set of spectral sensitivities of 111 cameras was collected from four publicly available databases. It was proposed to weight the spectral sensitivities in the database according to the similarities with those of the test camera. The similarity was evaluated by the reciprocal predicted errors of camera responses. Thus, a set of dynamic principal components was generated from the weighted spectral sensitivity database and served as the basis functions to estimate spectral sensitivities. The test stimuli included self-luminous colors from a multi-channel LED system and reflective colors from a color chart. The proposed method was tested in both the simulated and practical experiments, and the results were compared with the classical PCA method, three commonly used basis function methods (Fourier, polynomial, and radial bases), and a regularization method. It was demonstrated that the proposed method significantly improved the accuracy of spectral sensitivity estimation.

Sensor simulation using a spectrum tunable LED system.

This study developed a method to simulate the sensor responses and verify the effectiveness on spectral reconstruction by a spectrum tunable LED system. Studies have shown that the spectral reconstruction accuracy could be improved by including multiple channels in a digital camera. However, the real sensors with designed spectral sensitivities were hard to manufacture and validate. Therefore, the presence of a quick and reliable validation mechanism was preferred when performing evaluation. In this study, two novel approaches, i.e., channel-first and illumination-first simulations, were proposed to replicate the designed sensors with the use of a monochrome camera and a spectrum-tunable LED illumination system. In the channel-first method, the spectral sensitivities of three extra sensor channels were optimized theoretically for an RGB camera and then simulated by matching the corresponding illuminants in the LED system. The illumination-first method optimized the spectral power distribution (SPD) of the lights using the LED system, and the extra channels could be determined accordingly. The results of practical experiments showed that the proposed methods were effective to simulate the responses of the extra sensor channels.

Estimation of the perceptual color gamut on displays.

A new method was developed to evaluate the perceived gamut of a display. A multispectral image of a white gypsum sphere was projected onto various highly chromatic lights, producing a series of images with distinct hue perceptions at the gamut boundary of displays. These images were subsequently used in a psychophysical experiment to examine the perceived color gamut. Afterwards, the visual results were further compared with the prediction results from various uniform color spaces (UCSs) and color appearance models (CAMs). The present results demonstrate that CAM16-UCS provides the most accurate prediction across the entire color gamut, whereas the cyan-to-blue region is more poorly predicted than the other hue regions for all CAMs and UCSs investigated.

Factors affecting colour matching between displays.

A colour matching experiment was conducted to study and observe metamerism between different displays. The goals were to investigate the parameters of the display primaries (spectral power distributions (SPDs)), display types (OLED and LCD), and the colour matching functions (CMFs). The results showed that the use of the CIE 2006 2° CMFs can give better agreement to the visual results, especially matching between OLED against LCD displays, mainly due to the SPDs of the primaries. The results also showed that a simple color correction model improved the matching performance between displays, regardless of the display type.

Parametric effects in color-difference evaluation.

An experiment was conducted to investigate three parameters affecting color-difference evaluation on a display: 4 sample sizes (2°, 4°, 10°, and 20°), 2 color-difference magnitudes (4 and 8 CIELAB units), and 2 separations (inclusion or exclusion of the separation line between two colors in a pair). Sample pairs surrounding 5 CIE recommended color centers were prepared. In total, 1120 sample pairs of colors were assessed 20 times using the grey-scale method. The experimental results were used to reveal various parametric effects and to verify the performance of different color matching functions (CMFs) and four color difference formulae and uniform color spaces. It was found that there was little difference in terms of ΔE values calculated using different CMFs for all the color models tested. A parametric formula was proposed to predict three parametric effects for sample pairs having no-separation line: 1) differences in sample size, 2) media (surface and self-luminous colors), and 3) color-difference magnitudes.

Method for developing and using high quality reference images to evaluate tone mapping operators.

With the advancement of imaging technology, high dynamic range (HDR) images can now be captured and displayed to produce realistic effects. Tone mapping operators (TMOs) are used to map HDR radiance to the displayable range. A reliable TMO would play a significant role in the accurate reproduction of HDR scenes. The present study aimed to establish an image quality metric based on external references to evaluate various TMOs. Two psychophysical experiments were conducted to develop reference images and to investigate the performance of TMOs. In experiment 1, a set of high quality reference images was developed by rendering image features in terms of contrast, sharpness, and colorfulness, to achieve good rendering for each image. The images were used as reference in experiment 2 to evaluate the performance of 14 TMOs using a six-point categorical judgment method. The TMOs were evaluated using four scales, i.e., contrast, sharpness, colorfulness, and overall performance. The hierarchical relationship among TMOs was established. The results were further compared with previous studies, and high correlation was found between the current experiments and previous studies.

No-reference image quality metrics for color domain modified images.

Predicting the quality of natural images without using a reference image has always been a challenging task. Numerous approaches have been proposed in the past, but they mainly focused on spatial and frequency domain degradations like blur, noise, and compression. Image quality metrics (IQMs) in literature perform with quite a high accuracy for such types of degraded images. However, their performances are not good on the images modified in the color domain. In this study, psychophysical experiments were conducted to assess the quality of the color domain images. A new dataset was developed for this purpose. Additionally, a second dataset consisting of color domain modified images from the three previously published datasets were used in the psychophysical experiments. The newly developed dataset was then used to develop three IQMs based on absolute values, relative values, and statistical analysis of image color appearance attributes. Their performances were then evaluated together with five spatial domain IQMs from the literature using cross-database evaluation methodology. The results showed that the color-domain IQMs outperformed the other models. The absolute and relative attributes-based models, when combined, achieved the best performance. The present results suggest that more effort is needed to improve the performance of color domain IQMs for image quality estimation.

Developing a digital archive system for imperial Chinese robe in the Qing Dynasty.

The digital archive of cultural heritage provides new opportunities for the protection of the cultural heritage and the development of online museums. One of the essential requirements for the digitization is to achieve accurate color reproduction. Taking the Imperial Chinese robes in the Qing Dynasty as an example, this study aims to develop a digital achieve system to digitize the robes using a high-end imaging system and accurately reproduce their color properties on a display. Currently, there has been very limited study focused on the color reproduction of silk fabrics or other textile materials. The conventional color management process using a traditional color chart, however, may not be suitable for the reproduction of silk fabrics because they have very high gloss. To address this difficulty, a unique "Qianlong Palette" color chart, consisting of 210 silk fabric samples, has been specifically produced for optimizing the color reproduction of silk fabrics and a color image reproduction system has been developed for the digitization and archiving of the clothing fabric for the royal court. Color characterization models using both the "Qianlong Palette" color chart and the traditional color chart, and different mapping methods, are compared and the model with highest accuracy used in a self-programmed interface for automatically processing textile images in the future. Finally, the digital archive system has been validated using six garments of silk fabric relics. The color differences after the color image reproduction are all less than 3.00ΔE* ab , indicating acceptable color reproduction of the system. The images after color reproduction have also been evaluated subjectively by experts from the museum and the results are considered satisfactory. Our results show that the newly designed "Qianlong Palette" color chart exhibits superior performance over the conventional color chart in effectively predicting the color of the silk fabrics. The self-programmed graphical user interface for image color management can serve as a powerful tool to truly reproduce the color of various silk fabric relics in museums in the future and digitally archive those valuable cultural relics for different uses.

Preferred skin tones on mobile displays under illuminants having different correlated colour temperatures.

A psychophysical experiment was conducted to investigate preferred skin tones of 4 skin types under 5 illuminants varying in correlated colour temperatures. The experiments were performed on calibrated mobile display devices. Four facial skin tone images representing each skin type were captured and were rendered to 25 skin tone images to cover a large colour region. The facial skin tone images were assessed by a panel of 28 Chinese observers using an alternative forced choice psychophysical method. The ellipses based on observer preference rate were derived, and the preferred skin tone centres and 50% tolerance ellipse of different skin types under each test illuminants were obtained. According to the colour appearance shift of preferred skin tones under illuminants with varying CCTs, all data were transformed and compared in the a*b* plane under D65 and CIE 1931 Standard Colorimetric Observer condition. The results on the impact of illuminants on preferred skin tones were reported here. All types of skin tones had a good agreement under different illuminants.

Personalized image enhancement method for color deficient observers.

A personalized image enhancement method is proposed to improve color vision in hereditary color vision deficiency (CVD). It is divided into two stages: evaluation of CVD and gamut mapping for image enhancement. These two separate stages are connected via a psychophysical experiment, through which the deficiency test result expressed using the C-index can be further transformed into a physical parameter, namely the wavelength shift of the cone fundamental. Experiments conducted by the color-deficient observers (CDOs) validated this proposed method, and it is emphasized that the proposed method is just serving as a template for image enhancement. A more advanced simulation model, a more accurate assessment method, or a more sophisticated gamut mapping algorithm can yield a better result.

Accurate gamut boundary descriptor for displays.

A new gamut boundary descriptor (GBD) is presented in this paper. Unlike the traditional methods to perform sampling in RGB space and to interpolate the data in a uniform color space (UCS), the proposed method is designed in a reverse manner, i.e., to sample the data in UCS. This unique characteristic makes it simple and yields a smooth and accurate boundary. The proposed method can be divided into three simple steps. Firstly, coarse sampling is performed to make a rough estimate of the boundary. In step two, dense sampling is conducted to refine the boundary. Finally, the cusp is identified to achieve the accurate boundary. An experiment was carried out to compare the performance of the proposed method with the two commonly used SMGBD and Mountain Range methods. The results showed that the proposed method can give the most accurate and smooth boundary. It can be considered for practical applications.

Gamut mapping based image enhancement algorithm for color deficiencies.

This study presents an approach for enhancing color images for color vision deficiencies. The proposed approach is separated into three stages. First, the type and severity of a color deficient observer (CDO) were evaluated. Following that, the perceived color gamut was assessed using a physiologically-based color deficiency simulation model. Finally, images prepared for color normal observers (CNOs) were re-colored using a gamut mapping method to map colors from the gamut of a CNO to that of a CDO. Two psychophysical experiments were carried out to validate this method, and the results suggest that it is a promising solution for the CDOs. The unique feature of the present method is to include a gamut mapping method to enhance the color discrimination by preserving the perceived hue.

Evaluation of the colour quality of display primary: Part I. Chromaticity based methods.

It is a challenge to determine the RGB primaries when designing a display. A big issue is to estimate the colorimetric performance of the display. In this paper, a systematic method was proposed to determine the best RGB primaries for a display. Nine testing metrics were implemented and they were divided into two groups (the gamut metrics and the colour related metrics). They were adopted to evaluate the performance of 52 displays having different RGB primary combinations. The results verified the proposed method. Some of the testing metrics gave similar results and it should be sufficient to choose some of them to reveal the overall performance of a display.

Testing uniform colour spaces using colour differences of a wide colour gamut.

An experimental dataset, WCG, was assembled. The set includes 416 pairs of samples that surround 28 colour centres and covers a wide colour gamut. The data were used to test the performance of seven colour-difference models, CIELAB, CIEDE2000, CAM16-UCS, DIN99d, OSAGP, and ICTCP, Jzazbz. Colour discrimination ellipses were also fitted to compare the uniformity of the colour spaces. Different versions of the models were derived to improve the fit to the data, including parametric factors, kL, kC, and a power factor. It was found that the kL optimised CAM16-UCS, DIN99d, OSAGP models significantly outperformed the other colour models. In addition, the magnitude of the colour difference had an impact on visual assessment.

Color discrimination metric based on the neutrality of lighting and hue transposition quantification.

In this Letter, we propose a combined metric for quantifying the color discrimination capability of white light sources. This metric is based on considerations of human visual adaptation to daylight chromaticities, as well as on the concerns of the huge spectral diversity of modern light sources. Two existing metrics, Sneutral (degree of neutrality) by Smet et al. [Opt. Express22, 25830 (2014)OPEXFF1094-408710.1364/OE.22.025830] and Rd (hue transposition among color samples of the Farnsworth-Munsell 100 Hue color vision test) by Esposito and Houser [Lighting Res. Technol.51, 5 (2019)LRTEA90024-342610.1177/1477153517729200] were adopted, and their weights were determined by a meta-analysis of five groups of psychophysical data on color discrimination. The superiority of the newly proposed metric was demonstrated by 16 groups of psychophysical data from eight color discrimination studies, as well as by a comparison with 29 typical color quality metrics and their linear combinations.

Color difference evaluation for wide-color-gamut displays.

With the emerging demand for wide-color-gamut displays, an issue has been raised in which the commonly used color difference formulae or uniform color spaces that were derived based on the data produced in the relatively smaller color gamut could be unreliable for predicting color differences in the highly saturated color regions. A psychophysical experiment was carried out for evaluating color difference at a luminance level of 310cd/m2 on a wide-color-gamut display with an approximate DCI-P3 color gamut. Twelve color centers were selected to cover the entire gamut boundary. There were 192 pairs of samples over 12 color centers judged by 18 observers using the greyscale psychophysical method. The data set was used to test the performance of six uniform color spaces and color difference equations, CIELAB, CIEDE2000, CAM02-UCS, Jzazbz, ICTCP, and nICTCP, a newly revised ICTCP formula. The color discrimination ellipses were used to test local and global uniformity of color spaces and compared with previous studies. The results revealed that all formulae improved their performance to have a mean lightness parametric factor of about 0.5. CAM02-UCS significantly outperformed the others in overall, local, and global uniformity. The high-quality visual data set is recommended to evaluate or to derive color difference formulae for WCG applications in the future.

Observer metamerism to display white point using different primary sets.

Displays with different primary sets were found to introduce perceived color mismatch between stimuli that are computationally metameric and to affect the variations of the perceived color difference of metameric stimuli among observers (i.e., observer metamerism). In this study, computational analyses and psychophysical experiments were carried out to investigate the possibilities of increasing the color gamut area of a commercially available liquid crystal display (LCD) system using 16 three-primary sets, so that the perceived color difference of the white point between the system and the reference display and observer metamerism can be minimized. It was found the primary set with the peak wavelengths of 450, 525, and 665 nm was able to increase the sRGB color gamut by 72.1% in the CIE 1931 chromaticity diagram, which was found to have a strong correlation to the color volume of wide color gamut displays, while introducing the minimal color mismatch to the white point of the reference display and observer metamerism. The small white point color mismatch could be due to the similar wavelengths of the blue and green primaries in comparison to the reference display. In addition, the experiment results suggested that the CIE 2006 2° Color Matching Functions (CMFs) had better performance in characterizing the color match of the white point than the CIE 1931 2°, 1964 10°, and 2006 10° CMFs, which could be due to the fact that the stimulus used in the experiment only had a field of view (FOV) around 3.8°.

Hue linearity of color spaces for wide color gamut and high dynamic range media.

Hue linearity is an important property of uniform color spaces such that hues perceived to be similar should be located on a straight line, an iso-hue line, in that space. Previously derived hue linearity data only cover a limited color gamut. Two new psychophysical experiments were conducted that used a wide color gamut (WCG) and high dynamic range (HDR) display to extend the color range using both hue matching and unitary hue estimation methods. The new data were used to evaluate the CIELAB, CAM16-UCS, IPT, and Jzazbz uniform color spaces. The experimental results indicated that IPT and Jzazbz outperformed the other two, especially in the blue region. The same method was used to test these spaces using the other published data sets. The results from different data sets gave similar results. Finally, all results were combined to form a normalized data set to represent the data under HDR and WCG display conditions. Furthermore, the four unitary hue data can be used to develop or refine color appearance models.

Color-difference formula for evaluating color pairs with no separation: ΔENS.

All color-difference formulas are developed to evaluate color differences for pairs of stimuli with hairline separation. In printing applications, however, color differences are frequently judged between a pair of samples with no separation (NS) because they are printed adjacently on the same piece of paper. A new formula, ΔENS, has been developed for pairs of stimuli with NS. An experiment was conducted to investigate the effect of different color-difference magnitudes using sample pairs with NS. 1012 printed pairs with NS were prepared around 11 CIE recommended color centers. The pairs, representing four color-difference magnitudes of 1, 2, 4, and 8 CIELAB units were visually evaluated by a panel of 19 observers using the gray-scale method. Comparison of the present data based on pairs with NS, and previously generated data using pairs with hairline separation, showed a clear separation effect. A new color-difference equation for the NS viewing condition (ΔENS) is proposed by modifying the CIEDE2000 formula. The separation effect can be well described by the new formula. For a sample pair with NS, when the CIEDE2000 color difference is less than 9.1, a larger color difference leads to a larger lightness difference, but has no effect on the chromatic difference. When the CIEDE2000 color difference is greater than 9.1, the effect is the opposite. The new formula is recommended for future research to evaluate its performance in appropriate applications.

Development of a whiteness formula for surface colors under an arbitrary light source.

The whiteness specification is critically important in surface color industry, especially when fluorescent whitening agents (FWAs) are added to objects. The CIE whiteness formula, the most widely used whiteness formula, only characterizes the whiteness under CIE standard D65, which ignores the change of whiteness under different light sources due to the spectral content of the light sources. Though the adoption of a Chromatic Adaptation Transform (CAT02) in the CIE whiteness formula was found effective in recent studies, it failed to allow a comparison across different correlated color temperatures (CCTs). In this study, a haploscopic viewing condition was employed, with a D65 simulator in the left booth, for evaluating the whiteness of eight samples under different light sources in the right booth. The whiteness of the four samples under the D65 simulator was employed as a whiteness scale to aid the evaluation. Based on the experiment results, the characterization of whiteness for a surface under an arbitrary light source is proposed to use the CIE whiteness formula with the sample chromaticities being transformed using CAT02 and an adjusted degree of chromatic adaptation factor D.