Color Research and Application provides a forum for the publication of peer-reviewed research reviews, original research articles, and editorials of the highest quality on the science, technology, and application of color in multiple disciplines. Due to the highly interdisciplinary influence of color, the readership of the journal is similarly widespread and includes those in business, art, design, education, as well as various industries.

Color Research and Application is a forum for publishing high-quality peer-reviewed research reviews, original research articles, and editorials focused on the science, technology, and application of color across multiple disciplines. Given the highly interdisciplinary nature of color, the journal's readership is equally diverse, encompassing professionals in business, art, design, education, and various industries.

《Color Research and Application》是一个提供高质量同行评审研究综述、原创研究文章和社论的论坛，专注于颜色科学、技术及其在多个学科中的应用。由于颜色的高度跨学科影响，该期刊的读者群体也非常广泛，包括商业、艺术、设计、教育以及各个行业的专业人士。

Color Research and Application

Abstract Museums must choose illumination that will optimize observers' aesthetic experiences without compromising preservation of the artworks. Typical lighting is 3000 K at 200 lux. We examined the effects of color temperature by comparing the same “artwork” under several different illuminants (in side‐by‐side miniature museum rooms); for each painting, observers rated the preference for seeing it under one of the two illuminants; this was repeated for all pairings of illuminants. Our observers preferred higher color temperatures at about 3600 K. Between viewing trials observers' visual systems were adapted to a specific illuminant. This had no effect on preferred illumination of an artwork. To explore a wider range of artworks, we developed a set of numerical scales that could be applied directly to individual pictures; these were viewed, one at a time, in a single simulated room illuminated by one of a series of illuminants. Again, observers preferred a color temperature of about 3600 K. In both studies there was a small interaction between illuminant and color gamut of a given painting. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 121–127, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10231

Michael Scuello

Israel Abramov

James Gordon

Steven Weintraub

Color Research & Application

Museum lighting: Optimizing the illuminant

博物馆照明：优化光源

Abstract The contrast‐sensitivity function (CSF) is a measure of fundamental spatiochromatic properties of the human visual system. It is typically measured at the detection threshold for the psychophysically defined cardinal channels: luminance, red–green, and yellow–blue. Recent measurements of luminance contrast sensitivity show that the sensitivity of the luminance channel is less for chromatic stimuli than for achromatic stimuli. This chromatic effect has important implications for both human and machine vision. The chromatic effect on luminance contrast sensitivity has been modeled in this work based upon an existing model published by Barten. Barten's model was chosen as the starting point for this work because it is analytical, relatively simple, and can predict those effects that are important for image analysis. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 315–319, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20230.

Stephen Westland

Huw Owens

Vien Cheung

Iain Paterson-Stephens

Model of luminance contrast‐sensitivity function for application to image assessment

用于图像评估的亮度对比度敏感度函数模型

The principles that guided the founders of the CIE 1931 system for colorimetry are examined. The principles are applied to the Wright-Guild experimental determinations of the color mixture data to show in detail how and why each step in the development of the CIE 1931 system for colorimetry came about. These steps are examined in the light of 65 years advanced knowledge of colorimetry. The necessity for each of these principles in the modern world is examined critically to determine whether one might hold to the same principles if the system were being freshly formulated today. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 11–23, 1997.

Hugh S. Fairman

Michael H. Brill

Henry Hemmendinger

How the CIE 1931 color-matching functions were derived from Wright-Guild data

CIE 1931 色匹配函数是如何从Wright-Guild数据中推导出来的

ABSTRACT Color palette is a critical component of art, design, and lots of applications, providing the basis for organizing and utilizing colors to achieve specific objectives. However, generating color palettes from digital images presents unique challenges due to the complexity of colors in images. This review comprehensively investigates various techniques for generating color palettes from digital images and provides a thorough classification and discussion of these techniques from multiple perspectives. A color space must be selected to generate a color palette, and a generation method must be employed. This paper offers a concise overview of color spaces, an introduction to current palette generation methods, and an analysis of the metrics used to evaluate color differences between palettes. The review encompasses traditional manual methods and computer‐aided automation methods, further categorized as histogram‐based, clustering‐based, and neural network‐based methods. Discussion on the strengths, weaknesses, and applicability of existing methods are presented, and also opportunities for future research to enhance color palette generation from digital images are identified.

Yafan Gao

Jinxing Liang

Jie Yang

Color Palette Generation From Digital Images: A Review

数字图像调色板生成：综述

ABSTRACT Skin color constancy under nonuniform correlated color temperatures (CCT) and multiple light sources has always been a hot issue in color science. A more high‐quality skin color reproduction method has broad application prospects in camera photography, face recognition, and other fields. The processing process from the 14bit or 16bit RAW pictures taken by the camera to the final output of 8bit JPG pictures is called the image processing pipeline, in which the steps of the auto‐white balance algorithm have a decisive impact on the skin color reproduction result. The traditional automatic white balance algorithm is based on hypothetical statistics. Moreover, the estimated illuminant color is obtained through illuminant estimation. However, the traditional grayscale world, perfect reflector, and other auto‐white balance algorithms perform unsatisfactorily under non‐uniform or complex light sources. The method based on sample statistics proposes a new solution to this problem from another aspect. The deep learning algorithm, especially the generative adversarial network (GAN) algorithm, is very suitable for establishing the mapping between pictures and has an excellent performance in the fields of image reconstruction, image translation, defogging, and coloring. This paper proposes a new solution to this problem. The asymmetric UNet3+ shape generator integrates better global and local information to obtain a more refined correction matrix incorporating details of the whole image. The discriminator is Patch‐discriminator, which focuses more on image details by changing the attention field. The dataset used in this article is the Liverpool‐Leeds Skin‐color Database (LLSD) and some supplementary images, including the skin color of more than 960 subjects under D65 and different light sources. Finally, we calculate the CIEDE2000 color difference and some other image quality index between the test skin color JPEG picture corrected by the auto‐white balance algorithm and the skin color under the corresponding D65 to evaluate the effect of white balance correction. The results show that the asymmetric GAN algorithm proposed in this paper can bring higher quality skin color reproduction results than the traditional auto‐white balance algorithm and existing deep learning WB algorithm.

Sicong Zhou

Hesong Li

Wenjun Sun

Fanyi Zhou

Kaida Xiao

Auto‐White Balance Algorithm of Skin Color Based on Asymmetric Generative Adversarial Network

基于非对称生成对抗网络的肤色自动白平衡算法

ABSTRACT This study investigated how color variations in facial expressions influence our perception of emotions and health. Participants viewed color‐manipulated (CIE LAB color space) face images depicting seven emotional states and indicated their perceptions of each image's emotion and health. Our results suggest that facial color influences the perception of threat‐related emotions such as anger and disgust, as well as health perception. Increasing facial redness intensified the perception of anger, while increasing yellowness and lightness heightened the perception of disgust. Lightness affected perceptions of happiness and sadness, with lighter happy faces appearing happier and lighter sad faces appearing sadder. Additionally, enhancing redness and yellowness on faces led participants to perceive them as healthier. Our findings add to the existing literature and provide important insights into the role of colors in perceiving different emotions and health. These insights may significantly impact social interaction and communication, especially in situations where facial expressions play a critical role.

Faeze Heydari

Majid Khalili‐Ardali

Ali Yoonessi

Shades of Feeling: How Facial Color Variations Influence Emotional and Health Perception

情感的色彩：面部颜色变化如何影响情感和健康感知

ABSTRACT Two‐dimensional (2D) color appearance scales, including attributes such as whiteness, blackness, vividness, and depth, are closely aligned with our daily experiences and are thus highly sought after. This article presents a psychophysical experiment utilizing the magnitude estimation method under four levels of luminance (10, 100, 1000, and 10 000 cd/m 2 ). Observers evaluated both traditional one‐dimensional scales (brightness, colorfulness, and hue) and 2D scales (whiteness, blackness, vividness, and depth). The collected data were utilized to evaluate existing color appearance models, including CIECAM16, CAM16‐UCS, V * ab , and D * ab . Subsequently, new scales derived from the CAM16‐UCS model were developed to more accurately reflect the experimental data. These scales were further validated against independent data sets. The findings indicated that the scales developed from this study outperformed existing models when applied to external data sets. Moreover, Berns's scales for vividness and depth demonstrated strong predictive accuracy. Finally, four simple and accurate 2D scales are proposed.

Molin Li

Yuechen Zhu

Ming Ronnier Luo

Development of Vividness, Blackness, Depth, and Whiteness Scales Under High Range of Luminance Levels

高亮度水平下生动度、黑度、深度和白度量表的开发

ABSTRACT Color appearance characterization of stimuli is important in color science, with great efforts made to develop uniform color spaces (UCSs) and color appearance models (CAMs). These UCSs and CAMs, however, were mainly developed for stimuli with luminance below the diffuse white in a standard dynamic range (SDR) scene. This study was carefully designed to investigate the color appearance of self‐luminous highlight stimuli, in terms of relative brightness, in a high dynamic range (HDR) scene, and to see whether a new model for characterizing the brightness of highlights is needed. The observer viewed a dark stimulus (Stimulus 0) and a self‐luminous highlight (Stimulus 2) simultaneously under a certain diffuse white luminance level, which was an HDR scene, and adjusted the luminance of the other self‐luminous highlight (Stimulus 1) so that its brightness appeared in the middle of Stimuli 0 and 2. The luminance of Stimulus 2 was designed to as high as 49 000 cd/m 2 , the luminance contrast between Stimulus 2 and Stimulus 0 was as high as 72 045:1, and the diffuse white luminance level was designed to between 10 and 11 000 cd/m 2 . The results suggested that the UCSs and CAMs adopting a power function to characterize the non‐linear relationship between the relative luminance and perceived lightness (e.g., IPT, CIECAM02, and CIELAB) had much better performance to characterize the relative relationship of the lightness among the stimuli. Significant variations, however, were found among these UCSs and CAMs in characterizing the absolute magnitude of lightness and chroma, which merits further investigations.

Hongbing Wang

Minchen Wei

Characterization of Color Appearance of Self‐Luminous Highlights Under <scp>HDR</scp> Scenes, Part I: Brightness for Neutral Stimuli

高动态范围场景下自发光高光色彩外观特性研究，第一部分：中性刺激的亮度

Abbreviation	Color Res Appl
Journal Impact	1.18
Quartiles(Global)	OPTICS(Q4)

ISSN	0361-2317, 1520-6378
h-index	72

Publication Information	Publisher: John Wiley & Sons Inc.，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1976，Proportion of original research papers: 100.00%，Self Citation Rate:8.30%， Gold OA Rate: 16.54%
Average review cycle	网友分享经验：>12周，或约稿
Average recruitment ratio	网友分享经验：容易

Color Research and Application

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Museum lighting: Optimizing the illuminant

Model of luminance contrast‐sensitivity function for application to image assessment

How the CIE 1931 color-matching functions were derived from Wright-Guild data

Color Palette Generation From Digital Images: A Review

Auto‐White Balance Algorithm of Skin Color Based on Asymmetric Generative Adversarial Network

Auto‐White Balance Algorithm of Skin Color Based on Asymmetric Generative Adversarial Network

Color Palette Generation From Digital Images: A Review

Shades of Feeling: How Facial Color Variations Influence Emotional and Health Perception

Development of Vividness, Blackness, Depth, and Whiteness Scales Under High Range of Luminance Levels

Characterization of Color Appearance of Self‐Luminous Highlights Under HDR Scenes, Part I: Brightness for Neutral Stimuli