ECA-based generative adversarial network for multi-focus colour image fusion

Xiaojie Luo; Zhenkun Lu

doi:10.1117/12.2643626

12 October 2022 ECA-based generative adversarial network for multi-focus colour image fusion

Xiaojie Luo, Zhenkun Lu

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123423J (2022) https://doi.org/10.1117/12.2643626
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

In this paper, the idea of regression model is adopted to complete the fusion of multi-focus images through an end-to-end generative adversarial network (GAN). In the generator part, image features are extracted through multi-branch connection and dense connection technology. In the process of extracting high-dimensional image features, the ECA module is embedded to improve the capability of network. In the discriminator part, the idea of relative GAN is used to predict the relative authenticity between images. Due to the idea and reasonable network construction, the method proposed in this paper can obtain good results of image fusion. And the experimental results demonstrate that the one can also obtain fine results in objective evaluation, which is better than the compared algorithms.

Citation Download Citation

Xiaojie Luo and Zhenkun Lu "ECA-based generative adversarial network for multi-focus colour image fusion", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123423J (12 October 2022); https://doi.org/10.1117/12.2643626

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KEYWORDS

Image fusion

Image processing

Convolution

Image restoration

Feature extraction

Discrete wavelet transforms

Information fusion

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