Fusion of Multifucus Image with Noise Based on Adaptive Sparse and Low-Rank Representations


Xin Feng, Haifeng Gong, Guohang Qiu, Kaiqun Hu, Journal of Information Processing Systems Vol. 20, No. 5, pp. 602-616, Oct. 2024  

https://doi.org/10.3745/JIPS.04.0321
Keywords: Adaptive Sparse Representation, Image fusion, low-rank representation, Non-subsampled Shearlet Transform
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Abstract

Traditional multifucus image fusion often requires the inclusion of edge features, blurred details, and noise pollution when perturbed by noise. To address these problems, this study proposes a method for fusing noisy multifucus images using adaptive sparse and low-rank representations. The proposed method first decomposes the image into high- and low-frequency subband coefficients using a non-subsampled shearlet transform. Subsequently, the high-frequency energy components are fused and denoised using a low-rank representation. The corresponding fusion rules are then set using an adaptive sparse representation to fuse the low-frequency subband coefficients. The final fusion result is obtained by reconstructing the fused high- and low-frequency subband coefficients. Experimental results show that the proposed method outperforms traditional methods in terms of both subjective performance and objective indicators, making it a compelling fusion method for noisy multifucus images.


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Cite this article
[APA Style]
Feng, X., Gong, H., Qiu, G., & Hu, K. (2024). Fusion of Multifucus Image with Noise Based on Adaptive Sparse and Low-Rank Representations. Journal of Information Processing Systems, 20(5), 602-616. DOI: 10.3745/JIPS.04.0321.

[IEEE Style]
X. Feng, H. Gong, G. Qiu, K. Hu, "Fusion of Multifucus Image with Noise Based on Adaptive Sparse and Low-Rank Representations," Journal of Information Processing Systems, vol. 20, no. 5, pp. 602-616, 2024. DOI: 10.3745/JIPS.04.0321.

[ACM Style]
Xin Feng, Haifeng Gong, Guohang Qiu, and Kaiqun Hu. 2024. Fusion of Multifucus Image with Noise Based on Adaptive Sparse and Low-Rank Representations. Journal of Information Processing Systems, 20, 5, (2024), 602-616. DOI: 10.3745/JIPS.04.0321.