Image enhancement based on performed-FCMSPCNN
Jing Lian, Jibao Zhang, Jinying Liu, Jiajun Zhang, Hongyuan Yang · 2023
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 𝑊ijk1, 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.