Does an Expert Use Memory Colors to Adjust Images?

Boust, Clotilde; Cittadini, Ferruccio; Chouikha, Mohamed Ben; Brettel, Hans; Viénot, Françoise; Berche, Stéphane; Alquié, G.

doi:10.2352/cic.2004.12.1.art00060

Cited by 8 publications

(1 citation statement)

References 3 publications

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“…Therefore, memory and preferred colors were suggested as internal references for measuring color quality 4 , 5 and evaluating image quality 6 – 11 Smet et al 12 . investigated the relationship between memory color and color quality in both conventional and solid-state lamps.…”

Section: Introductionmentioning

confidence: 99%

Assessment of color reproduction in text-generated images of common natural objects (sky, grass, fallen leaves, rocks) based on memory color

Yan,

2024

J. Electron. Imag.

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By simulating the human brain, artificial intelligence-generated image models have the ability to learn various features from text memory, such as color, shape, and corresponding semantics. However, the quality of the generated images can be inconsistent due to various influencing factors. Therefore, the objective of this study is to evaluate the color quality of generated images depicting natural objects, such as sky, grass, fallen leaves, and rocks, based on memory colors. The memory color of the object in the reference image, obtained through the Baidu crawler, serves as the benchmark for comparison with the generated image. Alternatively, the color quality assessment of the generated images was performed by constructing H-S polar scatterplots, analyzing lab color distribution, and calculating average color differences. The GauGAN and ERNIE-ViLG models demonstrate higher accuracy in reproducing the memory color of the four objects, with the exception of the "fallen leaves" model, which exhibits more significant color differences. Furthermore, a survey was conducted to assess the recognition of color reproduction effects. The results indicate that the color presentation of the objects "grass," "fallen leaves," and "rocks" aligns with the observed color differences. These findings provide valuable insights for optimizing the color-quality rendering of text-generated image models.

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Section: Introductionmentioning

confidence: 99%

Assessment of color reproduction in text-generated images of common natural objects (sky, grass, fallen leaves, rocks) based on memory color

Yan,

2024

J. Electron. Imag.

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Color appearance rating of familiar real objects under immersive viewing conditions

Babilon

Khanh

2018

Color Research & Application

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With the concept of memory colors being considered to play a crucial role for many imaging and lighting applications, the questions how people assess the color appearance of familiar objects and what kind of fundamental characteristics can be derived from these assessments have extensively been studied in the past. However, all of the previous studies, the authors of this article are aware of, lack in realistic viewing and adaptation conditions. In the attempt of overcoming these deficiencies, a new experiment investigating the impact of long‐term memory on the color appearance ratings of 12 familiar test objects was performed. The pooled observer data were modeled in CIECAM02 color space using bivariate Gaussian functions whose centroids define the corresponding memory color centers for each test object. Comparisons with previous results obtained by Smet et al. revealed no significant differences in the reported memory color centers, but showed distinct deviations in the covariance matrices defining the shape of the fitted distribution functions. It is supposed that this new set of functions will lead to significantly different results when being used for the construction of an updated memory‐based color quality metric.

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Optimum memory color extraction for digital TVs based on genetic algorithm

Ryu

Kim

2011

IEEE Trans. Consumer Electron.

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Does an Expert Use Memory Colors to Adjust Images?

Cited by 8 publications

References 3 publications

Assessment of color reproduction in text-generated images of common natural objects (sky, grass, fallen leaves, rocks) based on memory color

Assessment of color reproduction in text-generated images of common natural objects (sky, grass, fallen leaves, rocks) based on memory color

Color appearance rating of familiar real objects under immersive viewing conditions

Optimum memory color extraction for digital TVs based on genetic algorithm

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