Multi-focus image fusion using residual removal and fractional order differentiation focus measure-Reference-Cited by-同舟云学术

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Multi-focus image fusion using residual removal and fractional order differentiation focus measure

Published:2024-02-15 Issue:4 Volume:18 Page:3395-3410
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Lu Jinbo,Tan Kunyu,Li Zhidan,Chen Jinling,Ran Qi,Wang Hongyan

Funder

Sichuan Provincial Key R&D Plan

the Special Project for City-College Science and Technology Strategic Cooperation of Nanchong City in 2022

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-024-03002-w.pdf

Reference49 articles.

1. Wang, C., Zang, Y., Zhou, D., Mei, J., Nie, R., Zhou, L.: Robust multi-focus image fusion using focus property detection and deep image matting. Expert Syst. Appl. 237 (2024)

2. Wang, Z., Li, X., Duan, H., Zhang, X.: A self-supervised residual feature learning model for multifocus image fusion. IEEE Trans. Image Process. 31, 4527–4542 (2022)

3. Vasu, G.T., Palanisamy, P.: Gradient-based multi-focus image fusion using foreground and background pattern recognition with weighted anisotropic diffusion filter. Signal Image Video Process. 17, 2531–2543 (2023)

4. Liu, Y., Wang, L., Cheng, J., Li, C., Chen, X.: Multi-focus image fusion: a survey of the state of the art. Inf. Fusion 64, 71–91 (2020)

5. Tian, J., Chen, L.: Adaptive multi-focus image fusion using a wavelet-based statistical sharpness measure. Signal Process. 92, 2137–2146 (2012)

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