Error diffusion optimization to enhance the saturation of colored e-paper

Lin Shanling; Xie Xinxin; Lin Jianpu; Lin Zhixian; Guo Tailiang

doi:10.12086/oee.2024.230309

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LIN S L, XIE X X, LIN J P, et al. Error diffusion optimization to enhance the saturation of colored e-paper[J]. Opto-Electron Eng, 2024, 51(1): 230309. doi: 10.12086/oee.2024.230309

Citation:

LIN S L, XIE X X, LIN J P, et al. Error diffusion optimization to enhance the saturation of colored e-paper[J]. Opto-Electron Eng, 2024, 51(1): 230309. doi: 10.12086/oee.2024.230309

Error diffusion optimization to enhance the saturation of colored e-paper

1.
School of Advanced Manufacturing, Fuzhou University, Quanzhou, Fujian 362251, China
2.
Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou, Fujian 350116, China
3.
College of Physics and Telecommunication Engineering, Fuzhou University, Fuzhou, Fujian 350116, China

Fund Project: Project supported by National Key R&D Program of China (2022YFB3603705), National Natural Science Foundation of China (62101132), and Natural Science Foundation of Fujian Province (2020J01468)

More Information

^*Corresponding author: ljp@fzu.edu.cn

Received Date 20 December 2023

Revised Date 05 February 2024

Accepted Date 05 February 2024

Published Date 25 January 2024

Abstract

Abstract

To solve the problems of low color saturation and edge blurring caused by viscous resistance and other factors in color EPD, this paper proposes a color e-paper edge enhancement error diffusion algorithm based on HSL space to improve the display quality. This algorithm first uses an edge detection operator to obtain edge-enhanced images from denoised images. It combines edge-enhanced image pixel neighborhood average gray level, pixel and neighborhood gray level difference, and pixel neighborhood similarity to obtain new RGB image pixel value. Then, the new RGB image is processed by a threshold process to obtain a 16-level RGB image. Finally, the 16-level RGB image is converted to HSL space, and a conversion model between HSL and RGB color spaces is established. According to the brightness and saturation of the pixel, the adjustment factor is calculated to enhance the saturation of the RGB image. Compared with the traditional error diffusion algorithm, the signal-to-noise ratio PSNR of this algorithm is improved by 3.9%~26.7%, the UCIQE is improved by 10.1%~48.2%, and the SSIM is improved by 13.2%~25.4%. The subjective evaluation refers to the ITU-R BT.500-1 standard to design experiments and calculate Z scores. Finally, the image details and colors of the image processed by this paper algorithm are closer to the original image on the color e-paper, and the overall visual effect is better.
- color electrophoresis display /
- error diffusion /
- saturation /
- edge detection /
- image enhancement

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References

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Overview

Overview

Electrophoretic display has the similar reflectance and wide viewing angle characteristics as paper, and will not harm the eyes due to the absence of a backlight. At the same time, electrophoretic display has the advantages of low power consumption and bistability, so EPD is often used for e-books, shelf price tags, and billboards. The eye protection characteristics make it deeply loved by the public, so people have more expectations for color EPD. However, there are still problems of unclear details and color distortion in the display image.

There are three main forces involved in electrophoresis particles: the interaction force between particles, the viscous resistance of the solvent, and the electric field force. The time delay of the particles reaching the common electrode is caused by the uneven force between the three factors. The low color saturation of the image and the blurred loss of edge details affect the feelings of the EPD users.

In order to solve the above problems, this paper proposes a color e-paper edge enhancement error diffusion algorithm based on HSL space to improve the display quality. This algorithm first uses an edge detection operator to obtain edge-enhanced images from denoised images. It combines edge-enhanced image pixel neighborhood average gray level, pixel and neighborhood gray level difference, and pixel neighborhood similarity to obtain new RGB image pixel value. Then, the new RGB image is processed by a threshold process to obtain a 16-level RGB image. Finally, the 16-level RGB image is converted to HSL space, and a conversion model between HSL and RGB color spaces is established. According to the brightness and saturation of the pixel, the adjustment factor is calculated to enhance the saturation of the RGB image.

The results show that compared with other algorithms, the proposed algorithm improves the PSNR by 3.9%~26.7%, the saturation by 10.1%~48.2%, and the SSIM by 13.2%~25.4%. The edges and details of the image displayed by EPD are enhanced; the clarity and visibility of the image are improved. Better preserve the information and color of the original image. The EPD shows more parts of the image detail, which are fully enhanced. The colors of the image are closer to the original and more saturated. All these have brought a better visual experience to the users of EPD.