Medical Image Coloring Based on Gabor Filtering for Internet of Medical Things

Hong An Li, Jiangwen Fan, Keping Yu*, Xin Qi, Zheng Wen, Qiaozhi Hua, Min Zhang, Qiaoxue Zheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


Color medical images better reflect a patient's lesion information and facilitate communication between doctors and patients. The combination of medical image processing and the Internet has been widely used for clinical medicine on Internet of medical things. The classical Welsh method uses matching pixels to achieve color migration of grayscale images, but it exists problems such as unclear boundary and single coloring effect. Therefore, the key information of medical images after coloring can't be reflected efficiently. To address this issue, we propose an image coloring method based on Gabor filtering combined with Welsh coloring and apply it to medical grayscale images. By using Gabor filtering, which is similar to the visual stimulus response of simple cells in the human visual system, filtering in 4 directions and 6 scales is used to stratify the grayscale images and extract local spatial and frequency domain information. In addition, the Welsh coloring method is used to render the image with obvious textural features in the layered image. Our experiments show that the color transboundary problem can be solved effectively after the layered processing. Compared to images without stratification, the coloring results of the processed images are closer to the real image.

Original languageEnglish
Article number9106393
Pages (from-to)104016-104025
Number of pages10
JournalIEEE Access
Publication statusPublished - 2020


  • Gabor filter
  • Internet of medical things
  • Medical image colorization

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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