A multi-exposure image fusion method based on histogram matching and convolutional neural network

Xinli Zhu; Yasheng Zhang; Yuqiang Fang; Di Luo

doi:10.1117/12.3026611

27 March 2024 A multi-exposure image fusion method based on histogram matching and convolutional neural network

Xinli Zhu, Yasheng Zhang, Yuqiang Fang, Di Luo

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310506 (2024) https://doi.org/10.1117/12.3026611
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

For high dynamic range image reconstruction in dynamic scenes, this paper proposes a multi-exposure sequence image fusion method based on histogram matching and convolutional neural network. First, image alignment is performed on the reference image based on the histogram matching method. Then, a multi-exposure fusion model based on convolutional neural network is constructed for the aligned multi-exposure sequence images. Finally, the fusion model is trained based on the training data, and the multi-exposure sequence image fusion in dynamic scenes is realized. The experimental results show that the method proposed in this chapter effectively avoids the influence of dynamic scenes on the fusion of multi-exposure sequence images, and at the same time can generate high-quality fused images.

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

Citation Download Citation

Xinli Zhu, Yasheng Zhang, Yuqiang Fang, and Di Luo "A multi-exposure image fusion method based on histogram matching and convolutional neural network", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310506 (27 March 2024); https://doi.org/10.1117/12.3026611

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