Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model

Weijie Chen, Zhenhong Jia, Jie Yang, Nikola Kasabov

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Abstract

Compared with single-band remote sensing images, multispectral images can obtain information on the same target in different bands. By combining the characteristics of each band, we can obtain clearer enhanced images; therefore, we propose a multispectral image enhancement method based on the improved dark channel prior (IDCP) and bilateral fractional differential (BFD) model to make full use of the multiband information. First, the original multispectral image is inverted to meet the prior conditions of dark channel theory. Second, according to the characteristics of multiple bands, the dark channel algorithm is improved. The RGB channels are extended to multiple channels, and the spatial domain fractional differential mask is used to optimize the transmittance estimation to make it more consistent with the dark channel hypothesis. Then, we propose a bilateral fractional differentiation algorithm that enhances the edge details of an image through the fractional differential in the spatial domain and intensity domain. Finally, we implement the inversion operation to obtain the final enhanced image. We apply the proposed IDCP_BFD method to a multispectral dataset and conduct sufficient experiments. The experimental results show the superiority of the proposed method over relative comparison methods.
Original languageEnglish
Article number233
Pages (from-to)1-25
Journalremote sensing
Volume14
Issue number1
DOIs
Publication statusPublished - 5 Jan 2022

Bibliographical note

Funding Information:
Funding: This work was supported by the National Science Foundation of China (No. U1803261) and the International Science and Technology Cooperation Project of the Ministry of Education of the People’s Republic of China (No. 2016–2196).

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • multispectral image enhancement;
  • remote sensing; dark channel prior;
  • fractional differential
  • Fractional differential
  • Dark channel prior
  • Multispectral image enhancement
  • Remote sensing

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