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Image naturalness model based on prototypical memory colors (sky, grass, and skin)

Image naturalness model based on prototypical memory colors (sky, grass, and skin) Image naturalness is a potent attribute to enhance image quality, and it is related to people's perception of memory colors. Many previous experiments aimed to locate the memory colors on different media. Their findings indicate that the memory colors obtained vary between color patches and images and between experimental techniques. However, there were no satisfying models with appropriate memory color centers to scale the image naturalness. This study generated an image database including three prototypical memory colors images (sky, grass, and skin) and their local processed images. First, visual naturalness and preference data were collected from a psychophysical experiment. Then, the distribution of naturalness followed by memory color positions was analyzed. Based on the distribution pattern, the ellipsoid models for each prototypical memory color were established. The results from the present memory color centers were compared with those from the other studies. Results show that the present color centers always give better prediction accuracy in image naturalness models. Finally, an image preference model was developed based on the image naturalness and colorfulness. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Color Research & Application Wiley

Image naturalness model based on prototypical memory colors (sky, grass, and skin)

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References (23)

Publisher
Wiley
Copyright
© 2022 Wiley Periodicals LLC.
ISSN
0361-2317
eISSN
1520-6378
DOI
10.1002/col.22781
Publisher site
See Article on Publisher Site

Abstract

Image naturalness is a potent attribute to enhance image quality, and it is related to people's perception of memory colors. Many previous experiments aimed to locate the memory colors on different media. Their findings indicate that the memory colors obtained vary between color patches and images and between experimental techniques. However, there were no satisfying models with appropriate memory color centers to scale the image naturalness. This study generated an image database including three prototypical memory colors images (sky, grass, and skin) and their local processed images. First, visual naturalness and preference data were collected from a psychophysical experiment. Then, the distribution of naturalness followed by memory color positions was analyzed. Based on the distribution pattern, the ellipsoid models for each prototypical memory color were established. The results from the present memory color centers were compared with those from the other studies. Results show that the present color centers always give better prediction accuracy in image naturalness models. Finally, an image preference model was developed based on the image naturalness and colorfulness.

Journal

Color Research & Application – Wiley

Published: Aug 1, 2022

Keywords: image naturalness model; image quality assessment; memory colors

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