An image enhancement method of a SLFC-MSPCNN for Dunhuang Murals

Yutong Hou; Rongrong Jia; Jiajun Zhang; Jibao Zhang; Jing Lian

doi:10.1117/12.3035152

19 July 2024 An image enhancement method of a SLFC-MSPCNN for Dunhuang Murals

Yutong Hou, Rongrong Jia, Jiajun Zhang, Jibao Zhang, Jing Lian

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132130Q (2024) https://doi.org/10.1117/12.3035152
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Mural restoration has an extremely important significance in image restoration. Image enhancement aims to improve image quality, clarity or visualization. The pulse-coupled neural network (PCNN) is a single-layer neural network structure for artificial neural networks, with featuring nonlinear coupling modulation, synchronized pulses, and dynamic pulse excitation. The unique structure and working principle of PCNN enable it to perform well with strong spatial and temporal correlations in image enhancement aspect. The synaptic-linked-FCMSPCNN(SLFC-MSPCNN) is proposed in this paper, and achieves more effective control of neuron firing time by adjusting adaptive parameters. Through related experiments, The proposed SLFC-MSPCNN has good image enhancement performances comparing with popular previous image enhancement approaches in Dunhuang Murals.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yutong Hou, Rongrong Jia, Jiajun Zhang, Jibao Zhang, and Jing Lian "An image enhancement method of a SLFC-MSPCNN for Dunhuang Murals", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132130Q (19 July 2024); https://doi.org/10.1117/12.3035152

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KEYWORDS

Image enhancement

Image processing

Image quality

Neurons

Visualization

Digital image processing

Mathematical modeling

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