An effective underground image enhancement approach based on improved KinD network

Author:

Wang Zheng,Yang Shukai,Zhang Jiaxing,Ji Zhaoxiang

Funder

National Natural Science Foun-dation of China

Shaanxi Province Qin Chuang yuan “Scientists + Engineers” Team Construction

Publisher

Springer Science and Business Media LLC

Reference26 articles.

1. Long, M., Yeng, M., Ri, L.: The review of low-light image enhancement. J. Image Gr. 27(05), 1392–1409 (2022)

2. Shao, Q., Yang, T., Wei, Y.: Image enhancement algorithm of mine surveillance video using improved homomorphic filtering. J. Xi’an Univ. Sci. Technol. 42(6), 1205–1213 (2022)

3. Gong, Y., Xie, Y.: Research on coal mine underground image recognition technology based on homomorphic filtering method. Coal Sci. Technol. 51(03), 241–250 (2023)

4. Tian, F., Chen, T., Zhang, J.: Research on improved retinex-based image enhancement method for mine monitoring. Appl. Sci. 13(4), 2672 (2023)

5. Li, Y., Iv, L., He, L.: An improved enhancement algorithm of mine image based on retinex. Sci. Technol. Eng. 20(29), 12028–12034 (2020)

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