ZHANG Hui, HAN Xinning, HAN Huili. Infrared and Visible Image Fusion Based on a Rolling Guidance Filter[J]. Infrared Technology , 2022, 44(6): 598-603.
Citation: ZHANG Hui, HAN Xinning, HAN Huili. Infrared and Visible Image Fusion Based on a Rolling Guidance Filter[J]. Infrared Technology , 2022, 44(6): 598-603.

Infrared and Visible Image Fusion Based on a Rolling Guidance Filter

More Information
  • Received Date: March 10, 2021
  • Revised Date: April 11, 2021
  • The fusion image must be made more suitable for human visual perception and the problem of a poor fusion effect caused by light and weather must be solved. Therefore, this study proposes a fusion method of visible and infrared images based on a rolling guidance filter. First, guided filtering is used to enhance the content of the visible image. Then, a rolling guidance filter is used to decompose the visible and infrared images into small-scale, large-scale, and base layers. In the process of information synthesis of large-scale layers, the weighted least square fusion rule is used to solve the problem caused by different features of visible and infrared images, and to improve the visual effect of fusion images. In the process of fusion of the base layer, the optimized fusion rule of the visual saliency map is used to reduce the loss of contrast. Finally, the large-scale, small-scale, and base layers are merged into a fused image. The experimental results show that the proposed method improves the visual effect, detail processing, and edge protection.
  • [1]
    ZHANG H, MA X, TIAN Y S. An image fusion method based on Curvelet transform and guided filter enhancement[J]. Mathematical Problems in Engineering, 2020(4): 1-8(DOI: 10.1155/2020/9821715)
    [2]
    张慧, 常莉红, 马旭, 等. 一种基于曲波变换与引导滤波增强的图像融合方法[J]. 吉林大学学报: 理学版, 2020, 58(1): 113-119. https://www.cnki.com.cn/Article/CJFDTOTAL-JLDX202001018.htm

    ZHANG H, CHANG L H, MA X. An image fusion method based on Curvelet transform and guide filtering enhancement[J]. Journal of Jilin University: Science Edition, 2020, 58(1): 113-119. https://www.cnki.com.cn/Article/CJFDTOTAL-JLDX202001018.htm
    [3]
    张慧, 常莉红. 基于方向导波增强的红外与可见光图像融合[J]. 激光与红外, 2020, 50(4): 508-512. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202004021.htm

    ZHANG H, CHANG L H. Infrared and visible image fusion based on guided filtering enhancement[J]. Laser & Infrared, 2020, 50(4): 508-512. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202004021.htm
    [4]
    LIU Y, LIU S, WANG Z. A general framework for image fusion based on multi-scale transform and sparse representation[J]. Information Fusion, 2015, 24: 147-164. DOI: 10.1016/j.inffus.2014.09.004
    [5]
    LI Shutao, KANG Xudong, HU Jianwen. Image fusion with guided filtering[J]. IEEE Trans. Image Process, 2013, 22(7): 2864-2875. DOI: 10.1109/TIP.2013.2244222
    [6]
    Bavirisetti D P, XIAO G, ZHAO H, et al. Multi-scale guided image and video fusion: a fast and efficient approach[J]. Circuits System Signal Process, 2019, 38: 5576-5605. DOI: 10.1007/s00034-019-01131-z
    [7]
    GAN W, WU X, WU W, et al. Infrared and visible image fusion with the use of multi-scale edge-preserving decomposition and guided image filter[J]. Infrared Physics & Technology, 2015, 72: 37-51.
    [8]
    ZHANG Q, SHEN X, XU L, et al. Rolling guidance filter[C]//European Conference on Computer Vision, Springer, 2014: 815-830.
    [9]
    MA J, ZHOU Z, WANG B, et al. Infrared and visible image fusion based on visual saliency map and weighted least square optimization[J]. Infrared Physics & Technology, 2017, 82: 8-17.
    [10]
    ZHAI Y, Shah M. Visual attention detection in video sequences using spatiotemporal cues[C]//Proceedings of the 14th ACM International Conference on Multimedia, ACM, 2006: 815-824.
    [11]
    Stark J A. Adaptive image contrast enhancement using generalizations of histogram equalization[J]. IEEE Transactions on Image Processing, 2000, 9(5): 889-896. DOI: 10.1109/83.841534
    [12]
    Rizzi A, Gatta C, Marini D. A new algorithm for unsupervised global and local color correction[J]. Pattern Recognition Letters, 2003, 24: 1663-1677. DOI: 10.1016/S0167-8655(02)00323-9
    [13]
    ZHOU Z, WANG B, LI S, et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with gaussian and bilateral filters[J]. Information Fusion, 2016, 30: 15-26. DOI: 10.1016/j.inffus.2015.11.003
    [14]
    DONG Z, LAI C, QI D, et al. A general memristor-based Pulse coupled neural network with variable linking coefficient for multi-focus image fusion[J]. Neurocomputing, 2018, 308: 172-183. DOI: 10.1016/j.neucom.2018.04.066
    [15]
    ZHOU Z, DONG M, XIE X, et al. Fusion of infrared and visible images for night-vision context enhancement[J]. Applied Optics, 2016, 55(23): 6480-6489. DOI: 10.1364/AO.55.006480
    [16]
    ZHAI Y, Shah M. Visual attention detection in video sequences using spatiotemporal cues[C]//Proceedings of the 14th ACM International Conference on Multimedia, ACM, 2006: 815-824.
    [17]
    Nava R, Cristo´bal G, Escalante-Ramırez B. Mutual information improves image fusion quality assessments[EB/OL][2007-09-04]. https://spie.org/news/0824-mutual-information-improves-image-fusion-quality-assessments?SSO=1
    [18]
    WANG Q, SHEN Y, JIN J. Performance evaluation of image fusion techniques[J]. Image Fusion: Algorithms and Applications, 2008, 9(10): 469-492.
  • Cited by

    Periodical cited type(7)

    1. 张健,黄安穴. 基于划区域宇宙算法的红外与可见光图像融合研究. 光电子·激光. 2024(09): 962-970 .
    2. 高丽娜. 视觉传达技术下激光图像过度曝光自修复研究. 激光杂志. 2024(11): 100-105 .
    3. 龚循强,方启锐,侯昭阳,张智华,夏元平. 一种光学与合成孔径雷达影像融合去云方法. 光学学报. 2024(24): 193-204 .
    4. 邸敬,郭文庆,刘冀钊,廉敬,任莉. 基于NSCT域滚动引导滤波与自适应PCNN的医学图像融合. 计算机应用研究. 2023(08): 2520-2525+2530 .
    5. 张慧,韩新宁,韩惠丽,常莉红. 基于引导滤波二尺度分解的红外与可见光图像融合. 红外技术. 2023(12): 1216-1222 . 本站查看
    6. 钟荣军,付芸. 基于Gabor滤波和显著性检测的红外与可见光图像融合. 长春理工大学学报(自然科学版). 2023(06): 26-33 .
    7. 张慧,韩新宁,韩惠丽,常莉红. 基于引导滤波二尺度分解的红外与可见光图像融合. 红外技术. 2023(11): 1216-1222 . 本站查看

    Other cited types(1)

Catalog

    Article views (270) PDF downloads (54) Cited by(8)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return