The CIECAM02 color‐appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational ...failures can occur in certain cases such as during the image processing of cross‐media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16‐UCS uniform color space is proposed to replace the previous CAM02‐UCS space. A new complete solution for color‐appearance prediction and color‐difference evaluation can now be offered.
Color appearance models were developed to characterize the color attributes of stimuli under different viewing conditions based on data collected through magnitude estimation or color matching ...experiments. Although human beings experience very high light levels under daylight and the reproduction of colors under daylight is important in the color and imaging industries, the existing color appearance models were developed based on the data that were collected under the conditions with luminance levels below 700 cd/m2 due to the lack of facilities to produce stable illumination at high light levels. A recent study investigating color preference of an artwork under a wide range of light levels from 20 to 15 000 lx suggested that CIECAM02 cannot accurately characterize the color appearance under extremely high light levels. This study was designed to directly test the performance of CIECAM02 from 100 to 3500 cd/m2. Human observers performed color match for four hues under a series pairs of adapting conditions with a haploscopic viewing condition. It was found that CIECAM02 had the best performance in characterizing the hue angles but the worse performance in characterizing the brightness with a maximum underprediction around 200% across a wide range of luminance. This was mainly due to the fact that CIECAM02 was developed based on the data collected under relatively low adapting luminance levels. The color appearance model that was proposed to use the adapting luminance levels in characterizing the cone compression in the postadaptation process was found to have a much better performance in characterizing the brightness.
Based on previous visual assessments of 440 color pairs of 3D-printed samples, we tested the performance of eight color-difference formulas (CIELAB, CIEDE2000, CAM02-LCD, CAM02-SCD, CAM02-UCS, ...CAM16-LCD, CAM16-SCD, and CAM16-UCS) using the standardized residual sum of squares (
) index. For the whole set of 440 color pairs, the introduction of
(lightness parametric factor),
(exponent in total color difference), and
+
produced an average
decrease of 2.6%, 26.9%, and 29.6%, respectively. In most cases, the CIELAB formula was significantly worse statistically than the remaining seven formulas, for which no statistically significant differences were found. Therefore, based on visual results using 3D-object colors with the specific shape, size, gloss, and magnitude of color differences considered here, we concluded that the CIEDE2000, CAM02-, and CAM16-based formulas were equivalent and thus cannot recommend only one of them. Disregarding CIELAB, the average
decreases in the
+
-optimized formulas from changes in each one of the four analyzed parametric factors were not statistically significant and had the following values: 6.2 units changing from color pairs with less to more than 5.0 CIELAB units; 2.9 units changing the shape of the samples (lowest
values for cylinders); 0.7 units changing from nearly-matte to high-gloss samples; and 0.5 units changing from 4 cm to 2 cm samples.
A comprehensive color appearance model should be capable of predicting color appearance under a wide range of viewing conditions, including related and unrelated colors. The current CAM16 model was ...designed to predict the appearance of related colors and is in the process of becoming a CIE recommendation, to replace the current CIECAM02 model. This article describes an extension of CAM16 (named CAM20u) for predicting the brightness, hue quadrature, amount‐of‐white, and colorfulness attributes of unrelated colors. Its performance, together with that of other unrelated models, was tested based on the three available datasets. The results show that the CAM20u model significantly outperforms the others, especially for colorfulness and amount‐of‐white.
In this work, the validity of a chosen color appearance model, CIECAM02 is examined for perceived lightness and brightness of fluorescent samples against some near achromatic backgrounds. To this ...end, the visual assessment technique and the paired comparison method have been conducted and the results are compared to those obtained by CIECAM02 color appearance model. Opposed to the initial expectation, the results show that the CIECAM02 is not an adequate model for prediction of lightness and brightness of fluorescent samples over a set of gray backgrounds.
•Cortical entrainment to components of CIECAM02 were found in primary visual cortex.•For CIECAM02-a, the latency of this entrainment was found to be 35 ms.•For CIECAM02-A, the latency of this ...entrainment was found to be 75 ms.•No significant entrainment was found for either CIELAB-L or CIELAB-A.
In human visual processing, information from the visual field passes through numerous transformations before perceptual attributes such as colour are derived. The sequence of transforms involved in constructing perceptions of colour can be approximated by colour appearance models such as the CIE (2002) colour appearance model, abbreviated as CIECAM02. In this study, we test the plausibility of CIECAM02 as a model of colour processing by looking for evidence of its cortical entrainment. The CIECAM02 model predicts that colour is split in to two opposing chromatic components, red-green and cyan-yellow (termed CIECAM02-a and CIECAM02-b respectively), and an achromatic component (termed CIECAM02-A). Entrainment of cortical activity to the outputs of these components was estimated using measurements of electro- and magnetoencephalographic (EMEG) activity, recorded while healthy subjects watched videos of dots changing colour. We find entrainment to chromatic component CIECAM02-a at approximately 35 ms latency bilaterally in occipital lobe regions, and entrainment to achromatic component CIECAM02-A at approximately 75 ms latency, also bilaterally in occipital regions. For comparison, transforms from a less physiologically plausible model (CIELAB) were also tested, with no significant entrainment found.
Kljub tehnološkemu napredku zadnjih stoletij in desetletij se še vedno soočamo s problematiko prikaza in upodobitve barve v različnih medijih in ohranjanja zaznave barve. Ena od možnosti, za katero ...se lahko odločimo pri zagotavljanju stalne barvne zaznave, so modeli barvnega zaznavanja. Trenutno je aktualen CIECAM02, ki se še vedno ne uporablja v 3D računalniški grafi ki, s katero se vsak dan srečujemo. Namen raziskave je bil pregled barvnih prostorov v 3D računalniški grafiki, pregled reprodukcije barv in materialov, algoritmov za senčenje ter izbranih sodobnih tehnologij upodabljanja za doseganje korektne končne vizualizacije. V nadaljevanju smo želeli proučiti model barvnega zaznavanja CIECAM02 do te mere, da bi ga lahko uporabili v povezavi s 3D računalniško grafiko. V ta namen smo v programu Blender postavili testno sceno in jo upodobili s tremi upodobljevalniki: Blender Render in Cycles, ki sta že vgrajena, in z dodatkom Yafaray. Izkazalo se je, da CIECAM02 lahko uporabimo tudi v 3D prostoru in da z njegovo uporabo dobimo boljše rezultate ujemanja barv pri spremembi ozadja. Poleg tega smo ugotovili, da barv ne upodabljajo vsi upodobljevalniki enako. Omenjena raziskava je aktualna za vse, ki želijo svoje dvo- ali tridimezionalne izdelke predstaviti s pomočjo 3D računalniške grafike, torej tudi za področje vizualizacij oblačil in tekstilnih izdelkov, ki se uporabljajo pri modnem oblikovanju in oblikovanju interjerjev, avtomobilski, navtični in letalski industriji ter tudi širše, kjer so dovršene 3D vizualizacije tekstilij in oblačil nepogrešljivi element vizualnih in grafičnih komunikacij.
•Compensation method for Helmholtz-Kohlrausch (H-K) effect in CIECAM02 was proposed.•Psychophysical experiments were conducted under three surround conditions.•Our experimental results show that ...conventional CIECAM02 cannot reflect H-K effect.•Our method enables CIECAM02 universally applicable to wide color gamut displays.
This paper proposes a method of compensating for the Helmholtz-Kohlrausch (H-K) effect which is a factor not being concerned in CIECAM02. H-K effect refers to the color appearance phenomenon that colored light appears brighter than achromatic light of the same luminance. By the magnitude estimation method, the perceptual lightness of active matrix liquid crystal display (AMLCD) is investigated. The results show that the lightness values predicted by CIECAM02 are lower than perceptual lightness values evaluated by the psychophysical experiments because of the H-K effect. The results on MobileCAM-v2, which is a refined version of CIECAM02, are investigated, as well. Since the color gamut of the display has been widening, the compensation for the H-K effect has also been increasingly important. In this paper, the method to compensate for the H-K effect in CIECAM02 is proposed. By modifying Fairchild’s equation, which is previously announced for CIELAB, CIECAM02 can be developed as a more complete color appearance model that can be universally applied to the display devices having a wide color gamut.
In the International Commission on Illumination (CIE) color appearance model CIECAM02, a modified hyperbolic function is used to represent luminance adaptation. The same nonlinear function is also ...used in the new color appearance model CAM16 Color Res Appl., 2017;42:703‐718. Although the modified hyperbolic function seems reasonable based on physiological evidence, it has an infinite slope at the origin, which causes instability for both the forward and inverse modes of the CIECAM02/CAM16 models. In this article, various possible extensions to the nonlinear luminance adaptation function in CIECAM02/CAM16 are reviewed and evaluated. Based on these investigations, the Gill extension to the hyperbolic function that is used to represent luminance adaptation Proceedings of 16th Color and Imaging Conference, pp. 327‐331, 2008, is recommended at both the lower end (q < qL) and the upper end (q > qU), where q is the appropriate Rc, Gc, Bc (or Rwc, Gwc, Bwc) response. In addition, the new recommended function can be readily inverted for use in the appropriate inverse appearance model. From an extensive analysis using available experimental data sets, we also propose that, for the lower and upper limits of the luminance range in the extended model, the values qL = 0.26 and qU = 150 be used, respectively.
Diabetic retinopathy (DR) is a complication of diabetes and is known as visual impairment, and is diagnosed in various ethnicities of the working-age population worldwide. Fundus angiography is a ...widely applicable modality used by ophthalmologists and computerized applications to detect DR-based clinical features such as microaneurysms (MAs), hemorrhages (HEMs), and exudates (EXs) for early screening of DR. Fundus images are usually acquired using funduscopic cameras in varied light conditions and angles. Therefore, these images are prone to non-uniform illumination, poor contrast, transmission error, low brightness, and noise problems. This paper presents a novel and real-time mechanism of fundus image enhancement used for early grading of diabetic retinopathy, macular degeneration, retinal neoplasms, and choroid disruptions. The proposed system is based on two folds: (i) An RGB fundus image is initially taken and converted into a color appearance module (called lightness and denoted as J) of the CIECAM02 color space model to obtain image information in grayscale with bright light. Afterwards, in step (ii), the achieved J component is processed using a nonlinear contrast enhancement approach to improve the textural and color features of the fundus image without any further extraction steps. To test and evaluate the strength of the proposed technique, several performance and quality parameters—namely peak signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR), entropy (content information), histograms (intensity variation), and a structure similarity index measure (SSIM)—were applied to 1240 fundus images comprised of two publicly available datasets, DRIVE and MESSIDOR. It was determined from the experiments that the proposed enhancement procedure outperformed histogram-based approaches in terms of contrast, sharpness of fundus features, and brightness. This further revealed that it can be a suitable preprocessing tool for segmentation and classification of DR-related features algorithms.
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