Color Appearance Model Research Articles

P‐3.12: FAAn Improved Color Restoration Method for High Dynamic Range Images

High Dynamic Range (HDR) images have entered our lives, but the HDR image may change its brightness and texture information after being compressed and layered, which makes the brightness distribution ratio of the HDR image deviate from the original image. Therefore, in order to ensure that the display effects before and after image processing are similar, it is necessary to restore the color of the image. This paper improves the traditional color restoration method based on image color appearance model. By introducing the latest CIE CAM16 color appearance model to perform color adaptation conversion on images, the problem of color appearance shift in the process of HDR image mapping is effectively improved.

Definition Problems of the Term “Lightness” in the History of its Development

The article is devoted to the research of changes in lighting terminology on the example of one of the main properties of colour – lightness. The article substantiates the importance of the qualitative definition of terms for the professional understanding of various aspects of colorimetry and possibility of usage colour appearance models (CAM). Examples and comparisons of the wording of theterms of the CIECAM02 system are given based on variants from International Lighting Vocabularies (ILV) different years of release. The next is an example of the history of the development of the terms associated with different conditions of perception and definition of brightness, in particular, such as “lightness” and “subjective brightness”. The importance of the clear agreement between the terms and their definitions for the understanding, use, and development of the modern models and systems of colour perception is substantiated. The English-language and the Russian-language scientific sources are considered. The analysis of which demonstrates the dynamics of changes in the understanding of the term “Lightness”. Special attention is paid to the fate of the term in the Russian-language lighting literature, discrepancies in the interpretation of the term in various sources are shown, which can lead to a misunderstanding of modern colour appearance models. The comparison of the interpretation of the term“Lightness” is reviewing based on the English-language and the Russian-language scientific sources. The comparison helps to identify the reasons that led to the problems of definitions and understanding of this term. In the conclusion, the authors invite experts to discuss lighting terminology and harmonize Russian-language lighting literature with English-language literature. Also substantiates the importance of the participation of lighting engineering scientists in translations of different scientific literary sources devoted to colour perception. It is proposed to continue work on improving, and possibly a special reprinting of translations for the better understanding in the Russian lighting engineering literature.

Preservation of Perceived Colorfulness of Down-Mapped, Hybrid Log-Gamma (HLG) to Standard Dynamic Range Content Using a Color Appearance Model (CAM)

Most of today’s high dynamic range (HDR) hybrid log-gamma (HLG) to standard dynamic range (SDR) conversions rely on a mathematical approach for color volume reduction from an International Telecommunication Union-Radioommunication (ITU-R) Recommendation BT.2100 container into an ITU-R BT.709 one, typically through “tone-mapping” applied to a luminance signal. However, this might not be the only plausible option for HLG to SDR conversion. A color appearance model (CAM) has been extended in this work to compute HLG to SDR down-mapping. This alternative down-mapping approach can be carried out through a CAM combined with a chromatic adaptation transform (CAT). The CAT transforms the image into a uniform color space (UCS), and the CAM calculates values of perceived quantities of the viewed media, such as lightness and colorfulness given specific display parameters. Perceptual quantities in the model are, for the most part, conserved to compute the down-mapping. This method has shown great promise in several natural images and colors, while having limitations with engineering test signals. SDR footage derived from an HDR capture using a CAM look-up table (LUT) results in natural pictures that are more visually accurate than those from conventional conversion technologies or SDR capture since many colors in nature exist outside of a BT.709 container. Other examples of down-mapping can be found in the ITU-R report BT.2446. Such down-mapping conversions attempt to maintain color fidelity between the two visual representations and are usually implemented in a 3D LUT. Such approaches, however, cannot take full account of psychovisual factors and may struggle to differentiate between colors such as yellow and brown that are similar in hue but vary in luminance. A CAM-based approach may not deliver mathematically ideal output values for artificial test patterns, so the article will also discuss what changes may need to be made to TV production workflows if the improvements offered by CAM-based down-mapping are to be fully realized.

Clinically Inspired Skin Lesion Classification through the Detection of Dermoscopic Criteria for Basal Cell Carcinoma.

Background and Objective. Skin cancer is the most common cancer worldwide. One of the most common non-melanoma tumors is basal cell carcinoma (BCC), which accounts for 75% of all skin cancers. There are many benign lesions that can be confused with these types of cancers, leading to unnecessary biopsies. In this paper, a new method to identify the different BCC dermoscopic patterns present in a skin lesion is presented. In addition, this information is applied to classify skin lesions into BCC and non-BCC. Methods. The proposed method combines the information provided by the original dermoscopic image, introduced in a convolutional neural network (CNN), with deep and handcrafted features extracted from color and texture analysis of the image. This color analysis is performed by transforming the image into a uniform color space and into a color appearance model. To demonstrate the validity of the method, a comparison between the classification obtained employing exclusively a CNN with the original image as input and the classification with additional color and texture features is presented. Furthermore, an exhaustive comparison of classification employing different color and texture measures derived from different color spaces is presented. Results. Results show that the classifier with additional color and texture features outperforms a CNN whose input is only the original image. Another important achievement is that a new color cooccurrence matrix, proposed in this paper, improves the results obtained with other texture measures. Finally, sensitivity of 0.99, specificity of 0.94 and accuracy of 0.97 are achieved when lesions are classified into BCC or non-BCC. Conclusions. To the best of our knowledge, this is the first time that a methodology to detect all the possible patterns that can be present in a BCC lesion is proposed. This detection leads to a clinically explainable classification into BCC and non-BCC lesions. In this sense, the classification of the proposed tool is based on the detection of the dermoscopic features that dermatologists employ for their diagnosis.

Extending CIECAM02 and CAM16 for the Helmholtz–Kohlrausch effect

AbstractIncreasing the purity of a visual stimulus increases its brightness, even if the stimulus luminance is held constant. This perceptual phenomenon is known as the Helmholtz–Kohlrausch (H–K) Effect. This paper reviews published experimental data and models of the effect. Using past experimental data, we derive a modification of the CIECAM02 and CAM16 color appearance models to account for the H–K effect and compare the proposed model to other models. Finally, we discuss the need for further experimental data on the H–K effect to refine the proposed model.

75‐1: Student Paper: Brightness and Vividness of High Dynamic Range Displayed Imagery

Metrics that predict the perceptual brightness of displayed imagery are vitally important, especially as wide color gamut, high dynamic range displays become more widespread. We implemented a color appearance modeling pipeline derived from the iCAM image color appearance framework and CAM76 color appearance model that allows for the accurate prediction of color appearance attributes, such as brightness, colorfulness, and vividness, of high dynamic range displayed imagery. Building on previous work on the Perceptual Contrast Length metric, we propose an updated Color Perceptual Contrast Length that correlates well with subjective ratings of display brightness.

P‐33: Measuring Color Strength for Wide Color Gamut OLEDs

With the release of high‐brightness and high‐chromatic OLED displays, color characteristics have become different from existing displays. The saturation of each pixel increases, and the luminance range widens, resulting in an H‐K effect that looks brighter than the actual luminance. This is a phenomenon that looks bright due to high purity and cannot be measured. In this paper, we intend to quantify the color characteristics of OLEDs using perceptual lightness predicted by color appearance model (CAM16) and measured luminance values. A new model to predict the H‐K effect was suggested as ‘Color Strength’ using the perceptual lightness and luminance. As a result, the values of QD OLED, W OLED, and LCD were compared by calculating the Color Strength.

Contributions of Surround Conditions on Color Appearance of Peridot Based on CAM16 Prediction

Peridot is the most abundant mineral on the earth and is widely used as gemstone in the world. In this paper, EMP analysis, UV-vis spectroscopy, and X-Rite SP62 spectrophotometer were used to study the chemical composition and color of the peridot. The CAM16 model was applied to predict the color appearance of peridot in different surrounding conditions. The chemical analysis and UV-vis spectra analysis showed there are seven narrow absorption bands at 414nm, 443nm, 481nm, 512nm, 557nm, 664nm and 684nm in peridot that should be assigned to the Fe chromophore. The color predictions indicated that the peridot will be brighter and more vivid when the luminance increases, which corresponds to Hunt Effect and Stevens Effect. Viewing surroundings have a great influence on the lightness and brightness in color appearance of peridot. CAM16 color appearance model is not suitable to predict the contributions of the light source on the color appearance of peridot due to the metameric effect. The windowing issue and the facets in peridot should be taken into consideration during the prediction calculation.

Brightness, lightness, colorfulness, and chroma in CIECAM02 and CAM16

AbstractIn the CIECAM02 and CAM16 color appearance models, brightness is computed as a nonlinear function of lightness. This paper traces the history of that nonlinearity to its roots in the Hunt color appearance model. A new, more robust, linear relationship between lightness and brightness is proposed. This new formula also prompts the reevaluation of the CAM16 equations for chroma, colorfulness, and saturation. The new formulas for these perceptual attributes are tested on experimental data from the Munsell color order system and the LUTCHI color appearance dataset and are compared to the performance of the original CAM16 equations.

Towards an image-based brightness model for self-luminous stimuli.

Brightness is one of the most important perceptual correlates of color appearance models (CAMs) when self-luminous stimuli are targeted. However, the vast majority of existing CAMs adopt the presence of a uniform background surrounding the stimulus, which severely limits their practical application in lighting. In this paper, a study on the brightness perception of a neutral circular stimulus surrounded by a non-uniform background consisting of a neutral ring-shaped luminous area and a dark surround is presented. The ring-shaped luminous area is presented with 3 thicknesses (0.33 cm, 0.67 cm and 1.00 cm), at 4 angular distances to the edge of the central stimulus (1.2°, 6.4°, 11.3° and 16.1°) and at 3 luminance levels (90 cd/m2, 335 cd/m2, 1200 cd/m2). In line with the literature, the results of the visual matching experiments show that the perceived brightness decreases in presence of a ring and the effect is maximal at the highest luminance of the ring, for the largest thickness and at the closest distance. Based on the observed results, an image-based model inspired by the physiology of the retina is proposed. The model includes the calculation of cone-fundamental weighted spectral radiance, scattering in the eye, cone compression and receptive field post-receptor organization. The wide receptive field assures an adaptive shift determined by both the adaptation to the stimulus and to the background. It is shown that the model performs well in predicting the matching experiments, including the impact of the thickness, the distance and the intensity of the ring, showing its potential to become the basic framework of a Lighting Appearance Model.

COLOR PERCEPTION ESTIMATIONS OF METAMERIC PAIRS UNDER DIFFERENT ILLUMINANCE LEVELS

LEDs or light emitting diodes of the lighting class dominate both the indoor and outdoor lighting industries today due to their accuracy and consumer-friendly color temperature. In the context of color science, it is necessary to analyze both the spectral power distribution of lighting and the human characteristics of color perception under these lights. In this article, we provide estimates of the appearance of eleven metameric pairs under LEDs with four correlated color temperatures and six illuminance levels, using color difference formulas based on the CIELAB, CAM02-UCS, and CAM16-UCS models to verify our estimates. We followed ASTM D4086 standard visual methods for detecting metamerism and for estimating the magnitude of a metameric color difference. Our investigations found that color appearance models are more reliable than CIELAB in evaluating color difference under various LED conditions. CAM16-UCS more accurately predicted the color difference estimates between all three formulas. Our comparative study confirms that the variation in the estimates with the CCT and illuminance levels of the LED sources depends on the color appearance model used. The results also showed that in order to determine the color difference of metameric pairs, optimal conditions regarding the colorimetric properties of the samples and the variability of the observer should be considered separately. We noticed an increasing correlation trend with increasing illuminance. However, there was no such increase or decrease trend in CCTs. The trend of the STRESS change in the color appearance models showed the influence of the chromatic adaptation, but the establishment of adaptation patterns is far beyond the scope of this work. Although our research has had limitations on correlated color temperature and illuminance, we believe that it can be beneficial for the lighting application to ensure correct lighting decisions when assessing the color differences of metameric pairs.

Image-brightness prediction model for wide-color-gamut displays based on Helmholtz–Kohlrausch (H–K) effect

A wider array of color gamut and higher luminance are increasingly offered by displays to provide users with immersive content. However, in the latest displays available, it is difficult to predict image brightness because the extensively used color appearance model is made based on a color patch whose color appearance is not the same as that of an image on the display. Therefore, in this study, a method of predicting image brightness on a display depending on its color gamut by quantifying the Helmholtz–Kohlrausch (H–K) effect is proposed. A method for accurately measuring image luminance is also presented. To verify the performance of the proposed model, a brightness matching experiment is performed under two different color gamut sizes. The experimental results confirm that the image appears brighter with the increase in color gamut due to the H–K effect, demonstrating that the proposed prediction model exhibits desirable performance. The proposed brightness prediction model, which includes the image experience in the color range, delivers better image quality to users.

Colour Quality Evaluation of Bluish-Green Serpentinite Based on the CIECAM16 Model

The CIECAM16 colour appearance model is currently a model with high prediction accuracy. It can solve the problem of predicting the influence of different observation conditions on the colour of gemstones. In this study, a computer vision system (CVS) was used to measure the colour of 59 bluish-green serpentinite samples, and the tristimulus values were input into the CIECAM16 forward model to calculate the colour appearance parameters of serpentinite under different surrounds, illuminances, and light sources. It was found that the darkening of the surround causes the lightness and brightness to increase. Pearson’s r of brightness and colourfulness with illuminance is 0.885 and 0.332, respectively, which predicts the Stevens and Hunt effects. When the light source changes from D65 to A, the calculated hue angle shifts to the complementary area of the A light source, which is contrary to the CVS measurement result. The D65 light source is more suitable for the colour presentation and classification of bluish-green serpentinite.

Effects of adapting luminance and CCT on appearance of white and degree of chromatic adaptation, part II: extremely high adapting luminance

In part I of this work [Opt. Express, 27 ,9276, (2019) 10.1364/OE.27.009276], we carried out an experiment to investigate the effects of adapting luminance and correlated color temperature (CCT) on degree of chromatic adaptation. Under the highest white luminance Lw of 900 cd/m2, an incomplete chromatic adaptation was still found under the 2700 and 3500 K adapting conditions. This motivated us to further increase the adapting luminance to investigate whether a complete chromatic adaptation cannot happen under a low adapting CCT (e.g., 2700 K). In this experiment, we investigated the degrees of chromatic adaptation under 12 adapting conditions, comprising four CCT (i.e., 2700, 3200, 4000, and 6500 K) and three white luminance levels (i.e., Lw of 1200, 2100, and 3000 cd/m2), by asking human observers to adjust the color appearance of a stimulus to the whitest. Such luminance levels of the adapting conditions were never investigated in the past and are assumed to introduce a complete chromatic adaptation. The results clearly show that an incomplete chromatic adaptation still happened under the adapting condition having a CCT of 2700 or 3200 K, though the luminance was so high. The adapting luminance and CCT were found to jointly affect the degree of chromatic adaptation, with a higher degree of adaptation under a higher adapting CCT or luminance level. When the adapting CCT was low (i.e., 2700 or 3200 K), the increase of adapting luminance was found to be able to increase the degree of adaptation more effectively. These findings suggest the necessity to revise the chromatic adaptation transforms (CAT) and color appearance models (CAM) for better characterizing the color appearance of stimulus under different adapting conditions.

A Comparison of Two Different Light Booths for Measuring Color Difference of Metameric Pairs

A standardized source of light is essential for visual color assessments, which is why lighting booths were developed. For the best results in visual assessment, it is important to consider the right choice of light source, the right viewing conditions, and the variability of the viewer. To date, many light booth technologies have been introduced to meet user demands. Since most of the light sources on the market are characterized by the designer or manufacturer, the resulting variations from booth-to-booth remain. In this study, we compared the performance of two standard light booths to assess the color difference of eleven metameric pairs. In this study, we checked an earlier technology-based light booth that is still used in the textile industry and contains illuminant A (Tungsten lamp) with CCT 2700 K, TL84 (tri-band fluorescent tube) with CCT 4000 K, and simulator D65 (CCT 6500 K) with a different light booth whose original light sources have been replaced by currently available LED retro kits from equivalent CCTs. As an inexperienced customer or industrial user, our question was, how important is this replacement? The results revealed that two different standard lighting technologies with similar CCTs cannot reproduce the same estimates because the light sources produced different SPDs. It is illustrating that caution is necessary when comparing results obtained from two different light booths containing light sources with similar CCTs but different SPDs. This comparative study suggested that the variability of the light sources’ SPDs or the observer or the sample should be modeled considering light booth’s technology to estimate its contribution to the overall variability. The close relationship between perceived and CAM02-UCS suggests that if both booths are used after the light sources have been calibrated, a formula based on color appearance models must be used to predict color appearance. To obtain better agreement between perceived and calculated color difference, one must need to avoid light booths with nominally white light sources.

Consideration of degree of chromatic adaptation for reproducing illuminated scenes

AbstractChromatic adaptation is an important mechanism in the human visual system, which affects the perceived color appearance of scenes and objects under the illumination. Recent studies, however, found that the degree of chromatic adaptation was significantly affected by the chromaticities of the adapting condition, which is not characterized in the existing chromatic adaptation transforms and color appearance models. This work was carefully designed to investigate how the degree of chromatic adaptation needs to be considered to reproduce the overall color tone of scenes under the illumination having a wide range of chromaticities. Human observers viewed a scene under 85 light settings, and then adjusted the color appearance of the scene image shown on a smartphone display to match that of the physical scene. The adjustment of the image color appearance was achieved by performing chromatic adaptation transform with different image white points. The results clearly showed how the degree of chromatic adaptation varied with the illuminant chromaticities, and how the image white point should be adjusted to reproduce the color tone of an illuminated scene.

Using Smooth Metamers to Estimate Color Appearance Metrics for Diverse Color-Normal Observers.

Color-normal subjects sometimes disagree about metameric matches involving highly structured SPDs, because their cone fundamentals differ slightly, but non-negligibly. This has significant implications for the design of light sources and displays, so it should be estimated. We propose a broadly applicable estimation method based on a simple adaptive "front-end" interface that can be used with any selected standard color appearance model. The interface accepts, as input, any set of color matching functions for the individual subject (for example, these could be that person's cone response functions) and also the associated tristimulus values for the test stimulus and also for the reference stimulus (i.e. reference white). The interface converts this data into tristimulus values of the form used by the selected color appearance model (which could, for example, be X, Y, Z), while also carrying out the needed transform, which is based on an estimate of the subject's likely previous long-term adaptations to their unique cone fundamentals. The selected standard color appearance model then provides color appearance data that is an estimate of the color appearance of the test stimulus, for that individual subject. This information has the advantage of being interpretable within that model's well-known color space. The adaptive front end is based on the fact that, for any selected input SPD and the subject's unique color matching functions, there can be many different SPDs that are metameric for that individual. Since observer-to-observer color perception differences are minimized for spectrally smooth SPDs, smooth metamers predict color appearances reasonably accurately.

Testing Colour Appearance Model Based UCS Using HDR, WCG and COMBVD Datasets

Two colour appearance models based UCSs, CAM16-UCS and ZCAM-QMh, were tested using HDR, WCG and COMBVD datasets. As a comparison, two widely used UCSs, CIELAB and ICTCP, were tested. Metrics of the STRESS and correlation coefficient between predicted colour differences and visual differences, together with local and global uniformity based on their chromatic discrimination ellipses, were applied to test models' performance. The two UCSs give similar performance. The luminance parametric factor kL, and power factor γ, were introduced to optimize colour-difference models. Factors kL and γ of 0.75 and 0.5, gave marked improvement to predict the HDR dataset. Factor kL of 0.3 gave significant improvement in the test of WCG dataset. In the test of COMBVD dataset, optimization provide very limited improvement.

Color Layer Scissioning in See-Through Augmented Reality

Color appearance of transparent objects is not adequately described by colorimetry or color appearance models. Despite the fact that the retinal projection of a transparent object is a combination of its color and the background, measurements of this physical combination fail to predict the saliency with which we perceive the object's color. When the perceive color forms in the mind, awareness of their physical relationship separates the physical combination into two unique perceptions. This is known as color scissioning. In this paper a psychophysical experiment utilizing a seethrough augmented reality display to compare virtual transparent color samples to real color samples is described and confirms the scissioning effect for lightness and chroma attributes. A previous model of color scissioning for AR viewing conditions is tested against this new data and does not satisfactorily predict the observers' perceptions. However, the model is still found to be a useful tool for analyzing the color scissioning and provides valuable insight on future research directions.

A new corresponding color dataset covering a wide luminance range under high dynamic range viewing condition

An experiment was carried out to investigate the change of color appearance for 13 surface stimuli viewed under a wide range of illuminance levels (15-32000 lux) using asymmetrical matching method. Addition to the above, in the visual field, observers viewed colours in a dark (10 lux) and a bright (200000 lux) illuminance level at the same time to simulate HDR viewing condition. The results were used to understand the relationship between the color changes under HDR conditions, to generate a corresponding color dataset and to verify color appearance model, such as CIECAM16.