Image Enhancement Algorithm Based on Image Spatial Domain Segmentation

Authors

  • Tianhe Yu Harbin University of Science and Technology, School of Measurement and Communication Engineering, Harbin 150080, China
  • Ming Zhu Harbin University of Science and Technology, School of Measurement and Communication Engineering, Harbin 150080, China

DOI:

https://doi.org/10.31577/cai_2021_6_1398

Keywords:

Mathematical model, frequency characteristics, regional segmentation, image enhancement

Abstract

This paper proposes an image enhancement algorithm based on the theory of image segmentation and image frequency. First, a mathematical model corresponding to the pixel frequency is established by using the difference of pigment values between the pixels in the image and the surrounding pixels (i.e., pixel receptive field). Then, the image is divided into the low frequency region (background area), low-medium frequency region (foreground area), medium-high frequency region (target area) and high frequency region (detail area) by a pixel frequency characteristic graph. Gamma correction, MSRCR, MSR, top hat+bottom hat are used for image enhancement for each area, and then the parts are merged. Three indicators of PSNR, SSIM, and MSE are introduced to evaluate the quality of the enhanced image. The results show that the image enhanced by this algorithm has the highest PSNR and SSIM values and the lowest MSE value, indicating that the enhancement effect of this algorithm is better. Compared with traditional algorithms, the image enhancement algorithm in this paper produces higher image quality and richer details.

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Published

2022-02-18

How to Cite

Yu, T., & Zhu, M. (2022). Image Enhancement Algorithm Based on Image Spatial Domain Segmentation. COMPUTING AND INFORMATICS, 40(6), 1398–1421. https://doi.org/10.31577/cai_2021_6_1398