Color Research and Application最新文献

Recent investigations into the Helmholtz–Kohlrausch (H–K) effect on modern displays have reported a complex, bimodal hue dependency that deviates from classical sinusoidal models. It has been hypothesized that this complexity might be an artifact of CIELAB non-uniformities rather than a genuine perceptual phenomenon. This study addresses this ambiguity through a comprehensive psychophysical experiment, with results analyzed in parallel using both CIELAB and the more uniform CAM16-UCS. The analysis reveals that the bimodal signature—characterized by distinct peaks in the cyan–blue and red–magenta regions—persists in CAM16-UCS, supporting its validity as a perceptual attribute for highly saturated stimuli. Furthermore, it is demonstrated that the eccentricity factor ($��e_t�$) within CAM16-UCS inherently captures the primary hue-dependent trend of the H–K effect. Leveraging this finding, two application-dependent models are proposed: a hue-invariant Simplified model suitable for general engineering workflows, and a Fourier model for high-precision applications requiring characterization of the secondary red–magenta peak. Both models are validated against eight datasets, demonstrating robust performance and offering a practical framework for lightness prediction in modern applications.

In recent years, gradient color products have gained popularity for their vibrant and eye-catching appeal, becoming a key visual trend across various design fields such as packaging, fashion, and furniture. Spearheaded by Pantone, these color schemes must harmonize with evolving public aesthetics and product design trends. Gradient-color products, compared to single-color ones, attract more consumer attention. However, designing effective gradient color schemes presents challenges, as they must quickly align with public preferences. This study proposes a gradient-color matching method tailored to these preferences, supported by an innovative aesthetic measurement formula. RGB and Pantone models, integrated with the Munsell color system, were used to create gradient color strips through arithmetic progression. Eye-tracking experiments identified visual hotspots in these strips, which informed the calculation of aesthetic values. Representative color points served as initial points for performing tricolor aesthetic measurements, thereby eliminating color schemes with insufficient aesthetic values. Running shoes served as design cases to apply and test the method. Public perception was evaluated through an aesthetic questionnaire, and Pearson correlation validated the results, showing a strong alignment with public aesthetics. The proposed method can assist future designers in developing gradient color recommendations for various products.

Color matching is a key element in product design that forms visual harmony, emotional connection, and spatial perception. As perfect balance between aesthetic value and perceptual continuity is still difficult to attain in view of differences in individual perception of color, this research seeks to provide a systematic and quantifiable approach to understanding how combinations of colors affect emotional expression and visual beauty in mechanical product design. The research uses the Aesthetic Measurement Model (AMM) with Markov decision-making theory to analyze 125 color palettes that fully cover the applied color coordinate system. The aesthetic measure theory is used to identify the unity and coherence of color aesthetics, and Markov decision theory is used to identify the connection among mechanical product images and color combinations, which results in five symbolic color variations from two representative samples. Statistical verification enhances the reliability and stability of results, validating the method connecting quantitative and qualitative color ratings. The AMM-Markov decision-making theory achieved a predictive accuracy of 96.5%, surpassing existing analyses and demonstrating improved capability in assessing product aesthetic quality. The research advances color-based design methods by integrating aesthetic measurement with decision-theoretic modeling, enhancing emotional appeal, visual beauty, and overall design quality of mechanical products.

Fairchild has argued that color spaces are of questionable utility for understanding perception. Here, we go through various concepts of mathematical spaces, ranging from abstract topological spaces to Euclidean ones, and discuss how color stimuli, color matches, and color perceptions can be adequately represented by means of some of these spaces. In particular, we argue that the set of color perceptions can be represented as a metric space that is homeomorphic to a neither open nor closed convex cone in an n-dimensional Banach space of equivalence classes of “generalized metamers.” Finally, for higher color metrics, we sketch how Riemannian geometry can be used to create a unified representation of color stimuli and color perceptions.

Color systems and atlases are critical tools for defining, organizing, and communicating colors across industrial, scientific, and artistic domains. While widely adopted systems—including Munsell, Natural Color System (NCS), DIN, Coloro, Pantone Fashion, Home + Interiors numbering system (Pantone FHI), and Sino Color Book (SCB)—leverage distinct organizational principles and application-specific advantages, their step sizes (spacing between adjacent chips) and uniformity (consistency of spacing) have not been compared. This study evaluates these metrics using four color difference formulas (CIELAB, CMC, CIEDE2000, and CAM16-UCS) to quantify step sizes and the coefficient of variation (CV) to assess uniformity. In terms of step size, key findings reveal that Coloro achieves the smallest median step size (with CIELAB values of 2.2, 1.6, and 1.8 in the Hue, Lightness, and Chroma attributes, respectively), but contains only a limited number of adjacent pairs. SCB ranks second (with CIELAB values of 2.0, 3.0, and 2.2 in the Hue, Depth, and Chroma attributes, respectively), yet it comprises a substantially larger number of pairs. In terms of uniformity, SCB exhibits superior uniformity in the Hue attribute. Both Munsell and DIN excel in uniformity in the Value/Darkness attribute. NCS leads in uniformity for the Chroma attribute. Crucially, no single system and atlas optimize across all attributes. These findings clarify system-specific strengths and highlight the challenge of integrating these strengths into a unified color system, while providing a foundation for future research in color order systems.

Much of the current research on display chromatic adaptation has predominantly used neutral colors as stimuli, while memory colors—critical for natural scene perception but under-researched—have been largely overlooked. Memory colors refer to the typical colors that are consistently associated with familiar objects in long-term memory (e.g., sky blue, skin tones). Given that users primarily interact with chromatic images rather than uniform neutral fields, distinct adaptation mechanisms may exist for these two stimulus categories. This study systematically investigates human chromatic adaptation to computer displays under 20 controlled adaptation conditions (correlated color temperature, CCT, from 2890 to 9000 K in five steps; deviation from the Planckian locus, Duv, from −0.02 to +0.02 in four steps) using both neutral and memory color stimuli. The results revealed that the degree of chromatic adaptation for both neutral and memory colors increased with higher CCT and that the relative magnitude of the D values for both types of stimuli was modulated by stimulus luminance. For the conditions with a same CCT, a Duv of +0.02 was found to provide a higher degree of chromatic adaptation, which differs from the findings in studies with neutral colors. The results were also used as corresponding colors to derive models of the degree of chromatic adaptation.