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Volume 45 Issue 10
Oct.  2023
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GAO Meiling, DUAN Jin, ZHAO Weiqiang, HU Qi. Near-infrared Image Colorization Method Based on a Dilated Global Attention Mechanism[J]. Infrared Technology , 2023, 45(10): 1096-1105.
Citation: GAO Meiling, DUAN Jin, ZHAO Weiqiang, HU Qi. Near-infrared Image Colorization Method Based on a Dilated Global Attention Mechanism[J]. Infrared Technology , 2023, 45(10): 1096-1105.
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Near-infrared Image Colorization Method Based on a Dilated Global Attention Mechanism

  • College of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130012, China

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  • Received Date: September 06, 2022
  • Revised Date: September 28, 2022
    Graphical Abstract
    • Abstract
  • A new generative adversarial network method is proposed for colorization of near-infrared (NIR) images, because current convolutional neural networks fail to fully extract the shallow feature information of images. This failure leads to miscoloring of the local area of the resultant image and blurring due to unstable network training. First, a self-designed dilated global attention module was introduced into the generator residual block to identify each position of the NIR image accurately and improve the local region miscoloring problem. Second, in the discriminative network, the batch normalization layer was replaced with a gradient normalization layer to enhance the network discriminative performance and improve the blurring problem caused by the colorized image generation process. Finally, the algorithms used in this study are compared qualitatively and quantitatively using the RGB_NIR dataset. Experiments show that the proposed algorithm can fully extract the shallow information features of NIR images and improve the structural similarity by 0.044, PSNR by 0.835, and LPILS by 0.021 compared to other colorization algorithms.
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    • References (24)
  • [1]
    戴康. 基于超像素提取和级联匹配的灰度图像自动彩色化[J]. 计算机与数字工程, 2019, 47(12): 3169-3172. https://www.cnki.com.cn/Article/CJFDTOTAL-JSSG201912044.htm

    DAI K. Automatic colorization of grayscale images based on superpixel extraction and cascade matching[J]. Computer and Digital Engineering, 2019, 47(12): 3169-3172. https://www.cnki.com.cn/Article/CJFDTOTAL-JSSG201912044.htm
    [2]
    曹丽琴, 商永星, 刘婷婷, 等. 局部自适应的灰度图像彩色化[J]. 中国图象图形学报, 2019, 24(8): 1249-1257. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201908004.htm

    CAO L Q, SHANG Y X, LIU T T, et al. Locally adaptive grayscale image colorization[J]. Journal of Image and Graphics, 2019, 24(8): 1249-1257. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201908004.htm
    [3]
    Tomihisa Welsh, Michael Ashikhmin, Klaus Mueller. Transferring color to greyscale images[C]//ACM TOG, 2002, 21(3): 277-280.
    [4]
    Reinhard E, Adhikhmin M, Gooch B, et al. Color transfer between images[J]. IEEE Computer Graphics and Applications, 2001, 21(5): 34-41.
    [5]
    冯佳男, 江倩, 金鑫, 等. 基于深度神经网络的遥感图像彩色化方法[J]. 计算机辅助设计与图形学学报, 2021, 33(11): 1658-1667. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJF202111003.htm

    FENG J N, JIANG Q, JINX, et al. Colorization method of remote sensing image based on deep neural network[J]. Journal of Computer-Aided Design and Computer Graphics, 2021, 33(11): 1658-1667. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJF202111003.htm
    [6]
    CHENG Z, YANG Q, SHENG B. Deep colorization[C]//Proceedings of the IEEE International Conference on Computer Vision, 2015: 415-423.
    [7]
    Isola P, ZHU J Y, ZHOU T, et al. Image-to-image translation with conditional adversarial networks[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 1125-1134.
    [8]
    Deblina Bhattacharjee, Seungryong Kim, Guillaume Vizier, et al. DUNIT: detection based unsupervised image-to-image translation[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020: 4787-4796.
    [9]
    万园园, 王雨青, 张晓宁, 等. 结合全局语义优化的对抗性灰度图像彩色化[J]. 液晶与显示, 2021, 36(9): 1305-1313. https://www.cnki.com.cn/Article/CJFDTOTAL-YJYS202109011.htm

    WAN Y Y, WANG Y Q, ZHANG X N, et al. Adversarial grayscale image colorization combined with global semantic optimization[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(9): 1305-1313. https://www.cnki.com.cn/Article/CJFDTOTAL-YJYS202109011.htm
    [10]
    左岑, 杨秀杰, 张捷, 等. 基于轻量级金字塔密集残差网络的红外图像超分辨增强[J]. 红外技术, 2021, 43(3): 251-257. http://hwjs.nvir.cn/article/id/a1540103-27df-466a-a058-1fd126ff5aec

    ZUO Q, YANG X J, ZHANG J, et al. Super-resolution enhancement of infrared images based on lightweight pyramidal dense residual networks[J]. Infrared Technology, 2021, 43(3): 251-257. http://hwjs.nvir.cn/article/id/a1540103-27df-466a-a058-1fd126ff5aec
    [11]
    姜玉宁, 李劲华, 赵俊莉. 基于生成式对抗网络的图像超分辨率重建算法[J]. 计算机工程, 2021, 47(3): 249-255. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC202103032.htm

    JIANG Y N, LI J H, ZHAO J L. Image super resolution reconstruction algorithm based on generative adversarial networks[J]. Computer Engineering, 2021, 47(3): 249-255. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC202103032.htm
    [12]
    张振江, 张宝金, 刘伟新, 等. 基于深度卷积网络的矿岩图像分割算法研究[J]. 采矿技术, 2021, 21(5): 149-152, 171. https://www.cnki.com.cn/Article/CJFDTOTAL-SJCK202105041.htm

    ZHANG Z J, ZHANG B J, LIU W X, et al. Research on mining rock image segmentation algorithm based on deep convolutional network[J]. Mining Technology, 2021, 21(5): 149-152, 171. https://www.cnki.com.cn/Article/CJFDTOTAL-SJCK202105041.htm
    [13]
    姚永康. 基于对抗式迁移学习的皮肤病变图像分割方法研究[D]. 西安: 西京学院, 2021.

    YAO Y K. Research on Skin Lesion Image Segmentation Method Based on Adversarial Transfer Learning[D]. Xi'an: Xijing University, 2021.
    [14]
    吴杰, 段锦, 董锁芹, 等. DFM-GAN网络在跨年龄模拟的人脸识别技术研究[J]. 计算机工程与应用, 2021, 57(10): 117-124. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202110015.htm

    WU J, DUAN J, TONG S Q, et al. DFM-GAN networks in cross-age simulation for face recognition[J]. Computer Engineering and Applications, 2021, 57(10): 117-124. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202110015.htm
    [15]
    刘高天, 段锦, 范祺, 等. 基于改进RFBNet算法的遥感图像目标检测[J]. 吉林大学学报: 理学版, 2021, 59(5): 1188-1198. https://www.cnki.com.cn/Article/CJFDTOTAL-JLDX202105026.htm

    LIU G T, DUAN J, FAN Q, et al. Remote sensing image target detection based on improved RFBNet algorithm[J]. Journal of Jilin University(Science Edition), 2021, 59(5): 1188-1198. https://www.cnki.com.cn/Article/CJFDTOTAL-JLDX202105026.htm
    [16]
    LI C, WAN D M. Precomputed real-time texture synthesis with markovian generative adversarial networks[C]//2016 European Conference on Computer Vision of IEEE, 2016: 702-716.
    [17]
    LI Y, CHEN Y, WANG N, et al. Scale aware trident networks for object detection[C]//2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019: 6053-6062.
    [18]
    Woo S, Park J, Lee J Y, et al. CBAM: convolutional block attention module[C]//2018 European Conference on Computer Vision, 2018: 3-19.
    [19]
    Ioffe S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift[C]//2015 Proceedings of the 32nd International Conference on International Conference on Machine Learning, 2015: 448-456.
    [20]
    Bhaskara V S, Aumentado-Armstrong T, Jepson A D, et al. GraN-GAN: piecewise gradient normalization for generative adversarial networks[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022: 3821-3830.
    [21]
    Brown M, Süsstrunk S. Multi-spectral sift for scene category recognition[C]//2011 IEEE Conference on Computer Vision and Pattern Recognition, 2011: 177-184.
    [22]
    Jason Antic. jantic/deoldify: a deep learning based project for colorizing and restoring old images (and video!)[J/OL] [2019-10-16]https://github.com/jantic/DeOldify.
    [23]
    LIANG W, DING D, WEI G. An improved dual GAN for near infrared image colorization[J]. Infrared Physics & Technology, 2021, 116(4): 103764-103777.
    [24]
    Perera P, Abavisani M, Patel V M. In2i: Unsupervised multi-image-to-image translation using generative adversarial networks[C]//2018 International Conference on Pattern Recognition, 2018: 140-146.
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