Laser & Optoelectronics Progress, Volume. 61, Issue 10, 1037010(2024)

Algorithm for Multifocus Image Fusion Based on Low-Rank and Sparse Matrix Decomposition and Discrete Cosine Transform

Yanqiong Shi1、*, Changwen Wang1, Rongsheng Lu2, Zhao Zha1, and Guang Zhu1
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei 230601, Anhui , China
  • 2School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei 230009, Anhui , China
  • show less

    To resolve the problems of scattered focus-edge blurring, artifacts, and block effects during the multifocus image fusion, an algorithm based on low-rank and sparse matrix decomposition (LRSMD) and discrete cosine transform (DCT) is designed to achieve the multifocus image fusion. First, the source images were decomposed into low-rank and sparse matrices using LRSMD. Subsequently, the DCT-based method was designed for detecting the focus regions in the low-rank matrix part and obtaining the initial focus decision map. The decision map was verified using the repeated consistency verification method. Meanwhile, the fusion strategy based on morphological filtering was designed to obtain fusion results of the sparse matrix. Finally, the two parts were fused using the weighted reconstruction method. The experimental results show that the proposed algorithm has the advantages of high clarity and full focus in subjective evaluations. The best results for the four metrics, including edge information retention, peak signal-to-noise ratio, structural similarity, and correlation coefficient in objective evaluations, improved by 62.3%, 6.3%, 2.2%, and 6.3%, respectively, compared with the other five mainstream algorithms. These improvement results prove that the proposed algorithm effectively improves focused information extraction from source images and enhances the focused edge detail information. Furthermore, the algorithm is crucial for reducing the artifact and block effects.

    Keywords
    Tools

    Get Citation

    Copy Citation Text

    Yanqiong Shi, Changwen Wang, Rongsheng Lu, Zhao Zha, Guang Zhu. Algorithm for Multifocus Image Fusion Based on Low-Rank and Sparse Matrix Decomposition and Discrete Cosine Transform[J]. Laser & Optoelectronics Progress, 2024, 61(10): 1037010

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Digital Image Processing

    Received: Aug. 4, 2023

    Accepted: Oct. 13, 2023

    Published Online: Apr. 29, 2024

    The Author Email: Shi Yanqiong (yqshi@ahjzu.edu.cn)

    DOI:10.3788/LOP231855

    CSTR:32186.14.LOP231855

    Topics