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Technology of Graphic & Image
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1901-1909

Unsupervised multi-focus image fusion based on target image prior information

Xie Ming
Qu Huaijing
Wu Yanrong
Wang Jiwei
Zhang Hanyuan
School of Information & Electric Engineering, Shandong Jianzhu University, Jinan 250101, China

Abstract

Multi-focus image fusion(MFIF) is an image enhancement method that combines the focused regions from different source images to form a fully sharp image. Currently, in the context of MFIF methods, there are two main challenges. First, traditional methods such as spatial domain approaches produce fusion images with high objective scores, but they suffer from strong defocus spread effects(DSE) and artifacts at the fusion boundaries. Second, deep learning methods lack a dataset generated from plenoptic cameras and require extensive manual parameter tuning, resulting in time-consuming training processes. To address these challenges, this paper proposed an unsupervised multi-focus image fusion method based on target image prior information. Firstly, it utilized the internal prior information of the source image itself and the external prior information of the initial fusion image generated by a spatial domain method as inputs for the G-Net and F-Net, respectively, both the G-Net and F-Net were components of the UNet-based deep image prior(DIP) network. Then, it introduced a reference mask generated by a spatial domain method to assist G-Net network for generating a guiding decision map. Finally, it used the decision map and the initial fusion image to jointly optimize the F-Net, producing the final fusion image. It conducted validation experiments on the Lytro dataset with real reference images and the MFFW dataset with strong DSE exhibiting in the fusion boundaries, and employed five widely used objective metrics for performance evaluation. The experimental results demonstrate that the proposed method significantly reduces the number of optimization iterations, and outperforms eight state-of-the-art MFIF approaches in terms of the subjective and objective performance evaluation, and especially shows superior performance on the datasets with strong DSE exhibiting in the fusion boundaries.

Foundation Support

国家自然科学基金资助项目(62003191)
山东省自然科学基金资助项目(ZR2014FM016)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0444
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 6
Section: Technology of Graphic & Image
Pages: 1901-1909
Serial Number: 1001-3695(2024)06-044-1901-09

Publish History

[2024-01-26] Accepted Paper
[2024-06-05] Printed Article

Cite This Article

谢明, 曲怀敬, 吴延荣, 等. 基于目标图像先验信息的无监督多聚焦图像融合 [J]. 计算机应用研究, 2024, 41 (6): 1901-1909. (Xie Ming, Qu Huaijing, Wu Yanrong, et al. Unsupervised multi-focus image fusion based on target image prior information [J]. Application Research of Computers, 2024, 41 (6): 1901-1909. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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