留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种基于参数自适应引导滤波的红外图像细节增强算法

欧阳慧明 夏丽昆 李泽民 何燕 朱晓杰 朱尤攀 曾邦泽 周永康

欧阳慧明, 夏丽昆, 李泽民, 何燕, 朱晓杰, 朱尤攀, 曾邦泽, 周永康. 一种基于参数自适应引导滤波的红外图像细节增强算法[J]. 红外技术, 2022, 44(12): 1324-1331.
引用本文: 欧阳慧明, 夏丽昆, 李泽民, 何燕, 朱晓杰, 朱尤攀, 曾邦泽, 周永康. 一种基于参数自适应引导滤波的红外图像细节增强算法[J]. 红外技术, 2022, 44(12): 1324-1331.
OUYANG Huiming, XIA Likun, LI Zemin, HE Yan, ZHU Xiaojie, ZHU Youpan, ZENG Bangze, ZHOU Yongkang. An Infrared Image Detail Enhancement Algorithm Based on Parameter Adaptive Guided Filtering[J]. Infrared Technology , 2022, 44(12): 1324-1331.
Citation: OUYANG Huiming, XIA Likun, LI Zemin, HE Yan, ZHU Xiaojie, ZHU Youpan, ZENG Bangze, ZHOU Yongkang. An Infrared Image Detail Enhancement Algorithm Based on Parameter Adaptive Guided Filtering[J]. Infrared Technology , 2022, 44(12): 1324-1331.

一种基于参数自适应引导滤波的红外图像细节增强算法

详细信息
    作者简介:

    欧阳慧明(1991-),男,白族,硕士,工程师。主要研究方向:红外成像系统设计及相关技术。E-mail: 799049681@qq.com

    通讯作者:

    周永康(1991-),男,硕士,工程师,红外成像系统设计及相关技术。E-mail:zyk1120102464@163.com

  • 中图分类号: TP751.1

An Infrared Image Detail Enhancement Algorithm Based on Parameter Adaptive Guided Filtering

  • 摘要: 图像分层滤波器中引导滤波器因其滤波保边效果好和计算复杂度低,在红外图像细节增强领域得到了广泛的研究与应用。但传统的引导滤波器固定的正则化参数ε不能在所有场景下都取得较好的滤波分层效果,所以本文提出基于局部方差的参数ε自适应算法,以提高引导滤波器场景适应性。此外本文进一步通过自适应参数ε值,提出了改进的基于噪声掩膜函数的细节层自适应增强算法,从而在有效抑制了图像噪声水平同时提高了算法在不同场景下的细节增强能力。
  • 图  1  不同能见度场景下ε的不同取值时引导滤波细节增强处理结果

    Figure  1.  Guided filtering detail enhancement processing results for different values of ε in different definition scenes

    图  2  细节纹理丰富图像和细节纹理不丰富图像局部方差直方图对比

    Figure  2.  Local variance histogram comparison of images with rich detail texture and images without rich detail texture

    图  3  本文自适应ε引导滤波细节增强算法处理结果(k取2)

    Figure  3.  Processing results of the adaptive ε-guided filtering detail enhancement algorithm in this paper (k = 2)

    图  4  不同能见度下基于GF & DDE细节层处理方法和本文细节层处理方法结果对比

    Figure  4.  Comparison of the results of the detail layer processing method based on GF & DDE and the detail layer processing method in this paper in different definition scenes

    图  5  场景一:细节丰富的清晰室外场景

    Figure  5.  Scene 1: a clear outdoor scene with rich details

    图  6  场景二:细节纹理模糊的室外场景

    Figure  6.  Scene 2: outdoor scene with hazy details and texture

    图  7  场景三:四杠靶图像

    Figure  7.  Scene 3: four-bar target image

    表  1  各算法在3个场景下处理图像的AG值和EMEE值结果对比

    Table  1.   Comparison of AG values and EMEE values of images processed by each algorithm in 3 scenes

    Method AGC CLAHE HALEQ BF & DRP GF & DDE Proposed
    Scene 1 AG 26.8014 59.8192 38.0070 95.156 78.1382 102.9149
    EMEE 142.5497 264.5845 157.5203 167.1697 185.0839 249.4993
    Scene 2 AG 21.9576 55.4266 29.5654 72.2097 60.2035 87.1753
    EMEE 28.4475 138.0465 86.2441 135.8672 106.4596 174.7866
    Scene 3 AG 25.2533 42.7458 42.9988 42.9236 37.0748 47.7793
    EMEE 16.7344 43.2476 33.1936 34.8786 28.7109 45.5171
    下载: 导出CSV
  • [1] 杨静, 李争. 一种基于双边滤波的红外图像细节增强方法[J]. 激光与红外, 2016, 46(4): 507-511. doi:  10.3969/j.issn.1001-5078.2016.04.025

    YANG Jing, LI Zheng. Detail enhancement method for infrared image based on bilateral filter[J]. Laser and Infrared, 2016, 46(4): 507-511. doi:  10.3969/j.issn.1001-5078.2016.04.025
    [2] 金伟其, 刘斌, 范永杰, 等. 红外图像细节增强技术研究进展[J]. 红外与激光工程, 2011, 40(12): 2521-2527. doi:  10.3969/j.issn.1007-2276.2011.12.040

    JIN Weiqi, LIU Bin, FAN Yongjie, et al. Research progress of infrared image detail enhancement technology[J]. Infrared and Laser Engineering, 2011, 40(12): 2521-2527. doi:  10.3969/j.issn.1007-2276.2011.12.040
    [3] 纪平, 胡学友, 张瑞琦, 等. 基于直方图均衡算法的图像增强技术研究[J]. 蚌埠学院学报, 2021, 10(2): 20-43. https://www.cnki.com.cn/Article/CJFDTOTAL-BBXY202102009.htm

    JI Ping, HU Xueyou, ZHANG Ruiqi, et al. Research on image enhancement technology based on histogram equalization algorithm[J]. Journal of Bengbu University, 2021, 10(2): 20-43. https://www.cnki.com.cn/Article/CJFDTOTAL-BBXY202102009.htm
    [4] Polesel A, Ramponi G, Mathews V J. Image enhancement via adaptive unsharp masking[J]. IEEE Transactions on Image Processing, 2000, 9(3): 505-510. doi:  10.1109/83.826787
    [5] Jobson D J, Rahman Z, Woodell G A. A multiscale retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE Transactions on Image Processing, 1997, 6(7): 965-976. doi:  10.1109/83.597272
    [6] 吴颖谦, 施鹏飞. 基于小波变换的低对比度图像增强红外[J]. 红外与激光工程, 2003, 32(1): 4-7. doi:  10.3969/j.issn.1007-2276.2003.01.002

    WU Yingqian, SHI Pengfei. Approach on image contrast enhancement based on wavelet transform[J]. Infrared and Laser Engineering, 2003, 32(1): 4-7. doi:  10.3969/j.issn.1007-2276.2003.01.002
    [7] ZHOU P, ZHAO B J. Novel scheme for infrared image enhancement based on contourlet transform and fuzzy theory[J]. Laser & Infrared, 2011, 41(6): 635-640. doi:  10.3969/j.issn.1001-5078.2011.06.008
    [8] HE K, SUN J, TANG X. Guided Image Filtering[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2013, 35(6): 1397-1409.
    [9] SONG Q, WANG Y, BAI K. High dynamic range infrared images detail enhancement based on local edge preserving filter[J]. Infrared Physics & Technology, 2016, 77: 464-473.
    [10] 葛朋, 杨波. 一种基于引导滤波图像分层的红外图像细节增强算法[J]. 红外技术, 2018, 40(12): 1161-1196. http://hwjs.nvir.cn/article/id/hwjs201812008

    GE Peng, YANG Bo. A detailed enhancement algorithm for infrared images based on hierarchical guided filtering[J]. Infrared Technology, 2018, 40(12): 1161-1196. http://hwjs.nvir.cn/article/id/hwjs201812008
    [11] 欧阳慧明, 李泽明, 周永康, 等. 非制冷红外图像动态范围压缩算法研究综述[J]. 红外技术, 2021, 43(3): 208-217. http://hwjs.nvir.cn/article/id/09092092-3317-453a-a6e3-01dff21a8e5f

    OUYANG Huiming, LI Zeming, ZHOU Yongkang, et al. A review of dynamic range compression algorithms for infrared images[J]. Infrared Technology, 2021, 43(3): 208-217. http://hwjs.nvir.cn/article/id/09092092-3317-453a-a6e3-01dff21a8e5f
    [12] Barash D, Comaniciu D. A common framework for nonlinear diffusion, adaptive smoothing, bilateral filtering and mean shift[J]. Image & Vision Computing, 2004, 22(1): 73-81.
    [13] HE K, SUN J, TANG X. Guided Image Filtering[M]//Computer Vision – ECCV 2010. Berlin Heidelberg: Springer, 2010.
    [14] 朱道广, 隋修宝, 朱才高, 等. 基于多尺度的高动态红外图像增强算法[J]. 红外技术, 2013, 35(8): 476-481. http://hwjs.nvir.cn/article/id/hwjs201308005

    ZHU Daoguang, SUI Xiubao, ZHU Caigao, et al. High dynamic infrared image enhancement algorithm based on multi-scale[J]. Infrared Technology, 2013, 35(8): 476-481. http://hwjs.nvir.cn/article/id/hwjs201308005
    [15] 樊启明. 基于滤波分层的红外图像增强算法研究[D]. 武汉: 华中科技大学, 2017.

    FAN Qiming. Research on Infrared Image Enhancement Algorithm Based on Filtering Layering[D]. Wuhan: Huazhong University of Science and Technology, 2017.
    [16] Pizer S M, Amburn E P, Austin J D, et al. Adaptive histogram equalization and its variations[J]. Computer Vis. Graph. Image Process, 1987, 39(3): 355-368.
    [17] 周永康, 朱尤攀, 曾邦泽, 等. 宽动态红外图像增强算法综述[J]. 激光技术, 2018, 42(5): 718-726. https://www.cnki.com.cn/Article/CJFDTOTAL-JGJS201805025.htm

    ZHOU Yongkang, ZHU Youpan, ZENG Bangze, et al. A review for high dynamic range infrared image enhancement algorithms[J]. Laser Technology, 2018, 42(5): 718-726. https://www.cnki.com.cn/Article/CJFDTOTAL-JGJS201805025.htm
    [18] Katsaggelos A K, Biemond J, Schafer R W, et al. A regularized iterative image restoration algorithm[J]. IEEE Transactions on Signal Processing, 1991, 39(39): 914-929.
    [19] Branchitta F, Diani M, Corsini G, et al. New technique for the visualization of high dynamic range infrared images[J]. Optical Engineering, 2009, 48(9): 096401.
    [20] LIU N, ZHAO D. Detail enhancement for high-dynamic-range infrared images based on guided image filter[J]. Infrared Physics & Technology, 2014, 67: 138-147. https://www.sciencedirect.com/science/article/pii/S1350449514001376
    [21] DUAN J, Bressan M, Dance C, et al. Tone-mapping high dynamic range images by novel histogram adjustment[J]. Pattern Recognition, 2010, 43(5): 1847-1862. https://www.sciencedirect.com/science/article/pii/S0031320309004518
    [22] Zuiderveld K. Contrast Limited Adaptive Histogram Equalization[M] //Graphics Gems IV, Academic Press Professional, . 1994: 474-485.
    [23] ZHANG F, XIE W, MA G, et al. High dynamic range compression and detail enhancement of infrared images in the gradient domain[J]. Infrared Physics & Technology, 2014, 67: 441-454. https://www.sciencedirect.com/science/article/pii/S1350449514001819
    [24] Agaian S S, Silver B, Panetta K A. Transform coefficient histogram-based image enhancement algorithms contrast entropy. [J]. IEEE Transactions on Image Processing, 2007, 16(3): 741-58. https://ieeexplore.ieee.org/document/4099384
  • 加载中
图(7) / 表(1)
计量
  • 文章访问数:  40
  • HTML全文浏览量:  12
  • PDF下载量:  28
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-04-18
  • 修回日期:  2021-06-23
  • 刊出日期:  2022-12-20

目录

    /

    返回文章
    返回