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A hole filling and optimization algorithm of remote sensing image based on bilateral filtering

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Abstract

In order to improve the quality of edge details of remote sensing image and solve the problem of large-scale holes and edge loss in remote sensing image, a new hole filling and optimization algorithm of remote sensing image based on bilateral filtering is proposed in this paper. The compensation function of similarity discrimination and Thiele continued fraction approximate exponential function are used to improve the traditional bilateral filtering algorithm. After the threshold is determined by histogram, the image is binarized to generate hole mask. The constraint term is added to the improved bilateral filtering algorithm for further optimization. According to the characteristics that pixels with the same color have the same gray value in a certain range, the hole area of remote sensing image is filled. The experimental results show that the algorithm can accurately fill the holes in the remote sensing image, not only restore the edge of the image, but also maintain the smoothness of the image. It has good filling performance, high image quality after optimization, image signal-to-noise ratio remains above 32 dB, and time complexity is low.

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Funding

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Authors and Affiliations

  1. Information Center, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei Province, China

    Wei Li

  2. Faculty of Applied Mathematics, Silesian University of Technology, 44100, Gliwice, Poland

    Marcin Wozniak

Authors
  1. Wei Li
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  2. Marcin Wozniak
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Contributions

Wei Li wrote the paper, Marcin Wozniak supervised the paper.

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Correspondence to Wei Li or Marcin Wozniak.

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Li, W., Wozniak, M. A hole filling and optimization algorithm of remote sensing image based on bilateral filtering. Mobile Netw Appl 27, 743–751 (2022). https://doi.org/10.1007/s11036-021-01904-4

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