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Colour enhancement of visual images in human-computer interaction interface under visual communication

Yue Du

International Journal of Product Development2025https://doi.org/10.1504/ijpd.2025.149701article
AJG 1
Weight
0.50

What the paper says

To enhance the vibrancy of hues and the structural coherence of visuals within interfaces for human-computer interaction, a methodology for augmenting the colouration of visuals in such interfaces is explored through the lens of visual communication. Initially, the noisy visuals of the human-machine interaction interface are refined using mathematical frameworks and sustained diffusion techniques. Subsequently, frame-by-frame scanning and three-dimensional spatial reconstruction are utilised to identify and refine the colour characteristics of the visuals in human-computer interaction interfaces. Ultimately, by integrating an ambient lighting model and employing spatial filtering, the visuals of human-computer interaction interfaces undergo colour enhancement to counteract the influences of surrounding light and motion-induced blur, thereby elevating the clarity of image hues and the overall visual fidelity. The experimental findings indicate that the approach detailed herein maintains high levels of colour and brightness saturation, with the Structural Similarity Index consistently registering at 0.97.

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https://doi.org/https://doi.org/10.1504/ijpd.2025.149701

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@article{yue2025,
  title        = {{Colour enhancement of visual images in human-computer interaction interface under visual communication}},
  author       = {Yue Du},
  journal      = {International Journal of Product Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijpd.2025.149701},
}

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Colour enhancement of visual images in human-computer interaction interface under visual communication

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.