A Fast Sand-Dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering

Yaqiao Cheng, Zhenhong Jia, Huicheng Lai, Jie Yang, Nikola Kasabov

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
331 Downloads (Pure)


The images captured in sand-dust weather have the characteristics of color deviation and low visibility, which seriously affect computer vision systems. To solve the above problems, we propose a fast and effective algorithm to enhance the images captured in sand-dust weather conditions. First, we compensate for the loss value in the blue channel. Then, white balancing technology is used to correct the color of the sand-dust-degraded image. Finally, guided image filtering is used to enhance the image contrast and edge accuracy, and an adaptive method is used to calculate the magnification factor of the detail layer to enhance the image detail information. The experimental results on a large number of sand-dust-degraded images show that the method can effectively recover the fading characteristics of sand-dust-degraded images in a short time and improve the clarity of the images. Experimental results via qualitative and quantitative evaluations demonstrate that the proposed method can significantly improve the images captured during sand-dust weather conditions, and the results are better than those of other methods.
Original languageEnglish
Pages (from-to)196690-196699
Number of pages9
JournalIEEE Access
Publication statusPublished (in print/issue) - 27 Oct 2020


  • send-dust degraded image
  • blue channel compensation
  • color correction
  • guided image filtering


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