Image enhancement based on performed-FCMSPCNN

Jing Lian; Jibao Zhang; JinYing Liu; Jiajun Zhang; Hongyuan Yang

doi:10.1117/12.2681600

1 June 2023 Image enhancement based on performed-FCMSPCNN

Jing Lian, Jibao Zhang, JinYing Liu, Jiajun Zhang, Hongyuan Yang

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 1271813 (2023) https://doi.org/10.1117/12.2681600
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

In Dunhuang mural image restoration, image enhancement techniques have effectively helped in image restoration. Based on pulse-coupled neural network (PCNN) has been widely used in image processing, in order to solve the low-lighting problem of Dunhuang mural images, on the basis of FC-MSPCNN model, the parameters such as synaptic weight matrix 𝑊_ijk1, link strength 𝛽, attenuation factor 𝛼 and attenuation adjustment parameter K are redefined in combination with adaptive parameter setting method, and the Performed-FCMSPCNN (PFC-MSPCNN) model. Finally, the linear transform, gamma transform, and histogram algorithms are used for image enhancement and compared with the PFC-MSPCNN model, respectively. It is verified that the PFC-MSPCNN model in this paper has a good enhancement effect on low-light images.

Citation Download Citation

Jing Lian, Jibao Zhang, JinYing Liu, Jiajun Zhang, and Hongyuan Yang "Image enhancement based on performed-FCMSPCNN", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 1271813 (1 June 2023); https://doi.org/10.1117/12.2681600

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