Color Appearance Model Research Articles

Colour difference detection algorithm for warp‐knitted fabric based on image colour appearance model

AbstractDetecting colour differences in warp‐knitting fabric is essential to ensure its quality. Machine vision algorithms are commonly used for automatic colour difference detection. However, the current algorithm directly extracts RGB (red, green, blue) colour stimulus values from the image without considering the image's colour attributes, leading to a significant error in colour difference detection. To solve this issue, a colour appearance model is introduced into the field of colour difference detection for warp‐knitted fabric. Initially, a colour appearance model based on CAM16 is established, and the critical parameters are calculated to obtain the colour appearance attribute of the fabric. The colour difference calculation formula is then constructed in the uniform colour space of CAM16‐UCS. A template selection algorithm based on principal component analysis was designed to select warp‐knitted cloth images with standard colours. Subsequently, a cloth colour difference detection algorithm was developed using the cloth colour profile model. The performance of the colour difference formula based on the colour profile model was evaluated using the PF/3 method. To compare the CIELab, CMC(2:1), and CIEDE2000 colour difference formulas, standardised residual sum of squares was used. The results indicated that the colour difference formula based on the colour‐appearance model is about 5.32% different from the visual colour difference perceived by the human eye. However, it can perform as well as the CMC(2:1) colour difference formula, which is widely used in the textile industry.

SiCAM: Spectral image Color Appearance Model

SiCAM: Spectral image Color Appearance Model

Simple color appearance model (sCAM) based on simple uniform color space (sUCS).

A new color appearance model named sCAM has been developed, including a uniform color space, sUCS. The model has a simple structure but provides comprehensive functions for color related applications. It takes input from either XYZ D65 or signals from an RGB space. Their accuracy has been extensively tested. sUCS performed the best or second-best to the overall 28 datasets for space uniformity and the 6 datasets for hue linearity comparing the state of the art UCSs. sCAM also performed the best to fit all available one- and two-dimensional color appearance datasets. It is recommended to have field tests for all color related applications.

The brightness of chromatic stimuli

AbstractWe present the results of a series of three brightness‐matching experiments which include a key refinement in this established psychophysical method. Constraining the chroma difference between pairs of stimuli matched in brightness allows us to use a novel calculus‐based approach to building a model of the brightness of chromatic visual stimuli and the Helmholtz‐Kohlrausch effect. The proposed models, compatible with the CIECAM16 color appearance model and CIELAB color space, are compared to other models of the Helmholtz‐Kohlrausch effect on these data and other past brightness‐matching studies. The proposed CIECAM16‐based model demonstrates the overall best performance on predicting the Helmholtz‐Kohlrausch effect in four newer data sets but overpredicts the weaker effect reported in three older data sets. The potential experimental factors in this divide between new and old studies are also discussed.

Brightness Prediction of Large Color Gamut Laser Display Devices.

A brightness-perceived color appearance model tailored for large gamut display devices, exemplified by laser displays, was investigated. Psychophysical experiments on the brightness matching of 30 color stimuli with achromatic white light were conducted by 16 observers. The analysis compares the performance of a number of existing color appearance models and equivalent luminance models in predicting brightness. None of the models performed acceptably due to a severe underestimation of the Helmholtz-Kohlrausch (H-K) effect. A modified model of perceived brightness based on CAM16, taking into account the H-K effect, is proposed. Evaluated by psychophysical experiments, the proposed model exhibits a superior performance compared to the preceding models, especially within the extensive color gamut range stipulated by BT.2020. The results help to optimize the design of laser displays with a wide color gamut and high perceived brightness.

Fundamental scales of hue appearance and discrimination

AbstractHue can be described with two types of scales. The first, for hue discrimination, is of the form of a hue angle metric such as found in the Munsell and CIELAB systems. The second, for hue appearance, is in the form of a hue quadrature metric as found in the NCS system and color appearance models such as CIECAM16. Any useful hue metric should also exhibit hue constancy – the important concept that stimuli of various lightness and saturation, but identical hue designations appear to be of the same hue. Hue angle in the IPT color model has repeatedly been shown to very well describe contours of constant hue and has been rigorously tested over more than two decades. However, the IPT model was not designed with hue spacing, for either discrimination or appearance, in mind. This paper describes the derivation of a fundamental and physiologically plausible model, called FHS for Fundamental Hue Scales, with predictors for both hue discrimination and hue appearance built directly from cone fundamentals and with hue linearity as good as that found in IPT. Such a model can be used with individual LMS color matching functions as the basis for the hue dimension of improved, and individualized, color appearance scales.

Domain and range of the CIECAM16 forward transformation.

The domain and range of the CIECAM16 forward transformation was numerically determined and visualized for CIE standard illuminants, using a linear programming approach that provides the gamuts and colour solids for optimum colours. The effect of the surround, adapting luminance, and luminance of the background on the range of the CIECAM16 forward transformation were individually analyzed, showing that their ranges increased when the surround changed from dark to dim or average, the adapting luminance increased, or the luminance of the background decreased. The proposed methodology for the determination and visualization of the domain and range of the CIECAM16 forward transformation can be used for any illuminant, as well as for CIECAM02, CAM16, CAM02-UCS and CAM16-UCS. The findings of this paper not only solve the long-term unresolved domain and range problems of the CIE colour appearance models, but also find applications in cross-media colour reproduction. Furthermore, it was also found that some non-CIE colours are inside the International Color Consortium Profile Connection Space (ICC PCS), and some CIE colours are not included in that space.

A model of colour appearance based on efficient coding of natural images.

An object's colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and "illusions" have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for in quantitative models of colour appearance. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band's lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next, we systematically test the model's ability to qualitatively predict over 50 brightness and colour phenomena, with almost complete success. This implies that much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a well-founded basis for modelling the vision of humans and other animals.

Evaluation of Color Difference Prediction with CIECAM16 using CIE 2- and 10-degree Observers

CIE has recently recommended a new color appearance model CIECAM16 to replace CIECAM02. It was also intended to recommend a uniform color space (UCS) based on CIECAM16, CIECAM16-UCS, for predicting color difference. However, there was a debate as to whether CIECAM16 can be used to predict color difference, since it takes tristimulus values calculated using the CIE 2∘ observer as input, while tristimulus values for color difference are usually calculated using the CIE 10∘ observer, as in the CIEDE2000 formula. Thus, further evidence is needed before CAM16-UCS can be recommended by the CIE as uniform color space. In this paper, we investigate the likely difference in color difference prediction when using CAM16-UCS, and its potential statistical significance. Firstly, the reflectance of each pair of color samples in the visual color difference datasets: BFD-P, Leeds, RIT-DuPont and Witt was generated based on the given tristimulus values. Then, color difference ΔE2, F and ΔE10, F, with F being the CAM16-UCS, can be computed under any illuminant using the 2∘ and 10∘ observers respectively. Comparison results showed that the difference between ΔE2, F and ΔE10, F was not statistically significant. Finally, both ΔE2, F and ΔE10, F were used to predict the visual color difference DV and the STRESS values between ΔE2, F and DV , and between ΔE10, F and DV respectively. Statistical tests showed that the differences between ΔE2, F and DV , and between ΔE10, F and DV were not significant. Hence this study shows that CAM16-UCS can be reliably used for predicting color difference. The findings are valuable for CIE to recommend CAM16-UCS as a uniform color space. Currently CIE TC1-98 is investigating the establishment of a new colorimetric system based on cone response tristimulus values LMS. It is expected that the reflectance datasets generated from the color difference datasets will be useful for the evaluation of any new colorimetric system.

Tone Mapping Operator for High Dynamic Range Images Based on Modified iCAM06.

This study attempted to solve the problem of conventional standard display devices encountering difficulties in displaying high dynamic range (HDR) images by proposing a modified tone-mapping operator (TMO) based on the image color appearance model (iCAM06). The proposed model, called iCAM06-m, combined iCAM06 and a multi-scale enhancement algorithm to correct the chroma of images by compensating for saturation and hue drift. Subsequently, a subjective evaluation experiment was conducted to assess iCAM06-m considering other three TMOs by rating the tone mapped images. Finally, the objective and subjective evaluation results were compared and analyzed. The results confirmed the better performance of the proposed iCAM06-m. Furthermore, the chroma compensation effectively alleviated the problem of saturation reduction and hue drift in iCAM06 for HDR image tone-mapping. In addition, the introduction of multi-scale decomposition enhanced the image details and sharpness. Thus, the proposed algorithm can overcome the shortcomings of other algorithms and is a good candidate for a general purpose TMO.

Heterochromatic brightness matching experiments to evaluate brightness prediction model including Helmholtz-Kohlrausch effect

In this study, the brightness matching experiment was conducted to obtain the equivalent luminance between chromatic and achromatic colors. Observers adjusted the luminance of achromatic colors until achromatic colors were perceived as having the same brightness with chromatic colors. A total of 285 chromatic colors having three different luminance levels, 30cd/m^2, 95cd/m^2, and 300cd/m^2 were used as the test colors. Twenty observers participated in this experiment repeating three times. The results showed that the brightness-to-luminance (B/L) ratio, where brightness means the luminance of achromatic color, increases as CIE 1976 saturation increases in all luminance levels indicating the Helmholtz-Kohlrausch effect. Also, as the luminance level of chromatic color increases, B/L ratio decreases. It is found that the existing color appearance models predicting the H-K effect overestimate the brightness increment by chroma compared to our new heterochromatic brightness matching data set.

Some recent advances in color science

We will discuss some of main topics in two recent publications on color from the International Commission on Illumination (CIE): CIE 015:2018 and CIE 248:2022. Regarding CIE 015:2018, it is the 4th edition of the most important CIE general publication on colorimetry, generally known as ‘CIE publication 15’. Among main novelties in CIE 015:2018 with respect to its previous 2004 edition, we can mention the introduction of the next four topics: 1) Cone-fundamental-based colorimetric observers; 2) New CIE illuminants (indoor daylight illuminants, smoothed daylight illuminants, illuminant E, and white LED illuminants); 3) The CIE colour appearance model CIECAM02; 4) The CIE 2017 color fidelity index. As a consequence of the active research on color appearance during the past few years, CIE 248:2022 proposed the CIECAM16 color appearance model for related colors and CIE 1931 standard colorimetric observer. In general, color appearance models provide a viewing-condition-specific method for the transformation of the tristimulus values X, Y, Z, to or from perceptual attribute correlates. CIECAM16 replaces CIECAM02 and may be useful for color management systems and image industries. CIECAM16 is simpler and maintains the predictions of experimental visual data made by CIECAM02. Finally, we will discuss advances in two issues related to color included in the current CIE Research Strategy: 1) A roadmap toward a new CIE colorimetry based on cone fundamentals, currently studied by CIE Technical Committee 1-98; 2) Color differences in tri-dimensional object colors and spatio-chromatic complexity, currently studied by CIE Technical Committees 8-17 and 8-14, respectively. In overall, we can conclude that color science is an active inter- and multi-disciplinary research field where optics continues playing a key role.

Fusion of colour contrasted images for early detection of oesophageal squamous cell dysplasia from endoscopic videos in real time

Standard white light (WL) endoscopy often misses precancerous oesophageal changes due to their only subtle differences to the surrounding normal mucosa. While deep learning (DL) based decision support systems benefit to a large extent, they face two challenges, which are limited annotated data sets and insufficient generalisation. This paper aims to fuse a DL system with human perception by exploiting computational enhancement of colour contrast. Instead of employing conventional data augmentation techniques by alternating RGB values of an image, this study employs a human colour appearance model, CIECAM, to enhance the colours of an image. When testing on a frame of endoscopic videos, the developed system firstly generates its contrast-enhanced image, then processes both original and enhanced images one after another to create initial segmentation masks. Finally, fusion takes place on the assembled list of masks obtained from both images to determine the finishing bounding boxes, segments and class labels that are rendered on the original video frame, through the application of non-maxima suppression technique (NMS). This deep learning system is built upon real-time instance segmentation network Yolact. In comparison with the same system without fusion, the sensitivity and specificity for detecting early stage of oesophagus cancer, i.e. low-grade dysplasia (LGD) increased from 75% and 88% to 83% and 97%, respectively. The video processing/play back speed is 33.46 frames per second. The main contribution includes alleviation of data source dependency of existing deep learning systems and the fusion of human perception for data augmentation.

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.

Constant Hue Loci in Rec. 2020 Gamut under an HDR Condition

Hue linearity is critically important to uniform color spaces and color appearance models. Past studies investigating hue linearity only covered relatively small color gamuts, which was generally acceptable for conventional display technologies. The recent development of HDR and WCG display technologies has motivated the development of new color spaces (e.g., IC<sub>T</sub>C<sub>P</sub> and J<sub>z</sub>a<sub>z</sub>b<sub>z</sub>). The hue linearity of these new color spaces, however, was not verified for the claimed HDR and WCG conditions, due to the lack of constant hue loci data. In this study, an experiment setup was carefully developed to produce HDR and WCG conditions, with the stimulus luminance of 3400 cd/m² and the diffuse white luminance of 1000 cd/m² and the stimulus chromaticities almost covering the Rec. 2020 gamut. The human observers performed a hue matching task, adjusting the hue of the test stimulus, with a hue angle step of 0.2°, at various chroma levels to match that of the reference stimulus at 21 different hues. The derived constant hue loci were used to test the various UCSs and suggested the need to improve the hue linearity of these spaces.

Color Appearance Characterization of Highlight Stimuli in HDR Scenes Across a Wide Range of Diffuse White Luminance

Various uniform color spaces and color appearance models were mainly developed for characterizing stimuli under a low dynamic range condition. Real scenes in daily life, however, are commonly high dynamic range (HDR), containing highlights with luminance beyond the diffuse white, whose color appearance characterization was never investigated in the past. This study was carefully designed to investigate the color appearance characterization of highlights in HDR scenes, covering extremely wide ranges of diffuse white luminance (up to 11000 cd/m<sup>2</sup>), stimulus luminance (up to 49000 cd/m<sup>2</sup>), stimulus chromaticities (reach Rec. 2020 gamut), and scene luminance contrast (up to 72045). The observers viewed two stimuli, including one highlight and one dark stimulus, in a viewing booth, and were asked to adjust the color appearance of another stimulus, so that the color differences between the adjusted stimulus to each of the other two stimuli appeared the same. The results clearly showed that none of the existing models, including the one (i.e., IC<sub>t</sub>C<sub>p</sub>) that was recently designed for HDR scenes, has a good performance. The models using a power function to characterize the non-linear compressive responses of the human visual system (i.e., CIELAB and IPT) had a slightly better performance. The findings provided some guidance for performing tone mapping and chroma/saturation adjustments, and clearly suggest the necessity to carry out further work to develop a better model for HDR scenes.

How Koreans Understand Colorfulness, Chroma, Vividness, and Depth

In this study, the relationships between chae-do, the commonly used Korean terminology to describe chromatic attributes, CIE definition for colorfulness, Munsell definition for chroma, Berns’ definition for CIELAB based vividness and depth are investigated. Although only the definitions were presented, without corresponding terminologies, the observers’ responses showed that chae-do is understood very similarly to the definitions of CIE colorfulness and Munsell chroma. Responses for the definitions of vividness and depth also showed high correlation with Berns’ CIELAB based vividness and depth predictions, which shows that definitions were well understood. No correlations were found between the definition of CIE colorfulness and the definition of vividness, which shows that the definition of vividness is understood differently to the definition of colorfulness. Comparing the response with color appearance model predictions, the responses showed good correlation with the predictions. Especially, colorfulness definition responses showed the highest coefficient correlation with CIELAB-based Berns’ depth prediction, implying the possibility of colorfulness predictor modification for better prediction. The findings can be further investigated to observers from other non-English speaking countries and collect meaningful cross-cultural color appearance data.

Reversibility of Corresponding Colors in Sensory Chromatic Adaptation

In colorimetry and color appearance modeling it is assumed that chromatic adaptation is reversible. Recent experimental results suggest that this might not be the case and that bidirectional models of chromatic adaptation might be needed. This paper describes a series of experiments designed to collect very-high precision corresponding colors data for sensory chromatic adaptation to test the hypothesis that chromatic adaptation is reversible for individual observers. The results indicate that there are small, but statistically significant, differences in corresponding colors due to changes in the previous state of adaptation. However the effect sizes are small and the number of repeated observations required to detect these differences is very large. Thus it is concluded that these differences are, while interesting, not problematic for practical colorimetry. In addition the application of the vk20 chromatic adaptation model for predicting such effects is further explored and its 15000K reference adaptation state is validated.

Information Flow in Biological Networks for Color Vision

Biological neural networks for color vision (also known as color appearance models) consist of a cascade of linear + nonlinear layers that modify the linear measurements at the retinal photo-receptors leading to an internal (nonlinear) representation of color that correlates with psychophysical experience. The basic layers of these networks include: (1) chromatic adaptation (normalization of the mean and covariance of the color manifold); (2) change to opponent color channels (PCA-like rotation in the color space); and (3) saturating nonlinearities to obtain perceptually Euclidean color representations (similar to dimension-wise equalization). The Efficient Coding Hypothesis argues that these transforms should emerge from information-theoretic goals. In case this hypothesis holds in color vision, the question is what is the coding gain due to the different layers of the color appearance networks? In this work, a representative family of color appearance models is analyzed in terms of how the redundancy among the chromatic components is modified along the network and how much information is transferred from the input data to the noisy response. The proposed analysis is performed using data and methods that were not available before: (1) new colorimetrically calibrated scenes in different CIE illuminations for the proper evaluation of chromatic adaptation; and (2) new statistical tools to estimate (multivariate) information-theoretic quantities between multidimensional sets based on Gaussianization. The results confirm that the efficient coding hypothesis holds for current color vision models, and identify the psychophysical mechanisms critically responsible for gains in information transference: opponent channels and their nonlinear nature are more important than chromatic adaptation at the retina.

Color appearance models CAM16, ZCAM and CAM20u for video applications

This work is devoted to the study of the possibility to use color perception models for processing streaming videos. The paper describes the principles of the control of image parameters which depend on the image adaptive properties. Methods for obtaining adaptive parameters such as brightness of adaptation, brightness of stimulus and brightness of background, as well as observation conditions are described. The CAM16 color perception model is accepted as the main one as well as the ZCAM and CAM20u models as the promising ones. The usability of color perception models is estimated, namely, the change of color rendering vector is assessed. It is shown that the chromaticity points that make up the color tone lines have a different nature of change – slope, shape. The estimates of the dependence of transmitted colors on lightness are provided. It is demonstrated that the lightness parameter is more non-linear character CAM20u as compared to the previous models.