Advanced Search
中文
Volume 46 Issue 1
Jan.  2024
Turn off MathJax
Article Contents
Abstract
References
Related Articles
MA Qun, ZHAO Meirong, ZHENG Yelong, SUN Lin, NI Feng. Infrared Image Detail Enhancement Based on Adaptive Conditional Histogram Equalization[J]. Infrared Technology , 2024, 46(1): 52-60.
Citation: MA Qun, ZHAO Meirong, ZHENG Yelong, SUN Lin, NI Feng. Infrared Image Detail Enhancement Based on Adaptive Conditional Histogram Equalization[J]. Infrared Technology , 2024, 46(1): 52-60.
shu

Infrared Image Detail Enhancement Based on Adaptive Conditional Histogram Equalization

  • 1.

    School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China

  • 2.

    Jinhang Institute of Technical Physics, Tianjin 300308, China

More Information
  • Received Date: December 05, 2022
  • Revised Date: February 14, 2023
    Graphical Abstract
    • Abstract
  • There are many problems with infrared images, such as low contrast, unclear details, and non-prominent edge features. To solve these problems, this study proposes an adaptive conditional histogram equalization algorithm for infrared image detail enhancement. First, the infrared image is decomposed into background and detail layers by a guided filter. Second, the combined adaptive threshold neighborhood condition histogram and contrast limited histogram equalization method are used to compress and enhance the gray level of the background image. Then a noise mask is constructed using the intermediate calculation results of the guided filter, which can effectively filter the background noise while enhancing the detail layer. Finally, the background and detail layer processing results are linearly fused to obtain a detail-enhanced infrared image. Subjective evaluation and objective data calculation show that the infrared image detail enhancement algorithm proposed in this paper realizes adaptation to various scenes without manual parameter adjustment, and can effectively enhance the image details and improve the overall contrast level of the image under the premise of suppressing noise. Embedded transplantation of the algorithm was performed, and the display effect and resource occupation show that the algorithm has strong engineering application prospects.
    • FullText(HTML)
    • References (19)
  • [1]
    刘珂, 王炜强, 李丽娟. 红外成像制导技术在反隐身空空导弹上的应用展望[J]. 航空兵器, 2022, 29(2): 60-65.

    LIU Ke, WANG Weiqiang, LI Lijuan. Application and prospect of infrared imaging guidance technology in anti-stealth air-to-air missiles [J]. Aero Weaponry, 2022, 29(2): 60-65.
    [2]
    袁盼, 谭竹嫣, 张旭, 等. 工业气体泄漏红外成像检测及差分光谱滤波检测方法研究[J]. 红外与激光工程, 2022, 51(8): 20210714.

    YUAN Pan, TAN Zhuyan, ZHANG Xu, et al. Research on infrared imaging detection and differential spectrum filtering detection methods for industrial gas leakage[J]. Infrared and Laser Engineering, 2022, 51(8): 20210714.
    [3]
    曹志伟. 车载图像行人检测关键技术研究[D]. 北京: 北京邮电大学, 2021.

    CAO Zhiwei. Research on Key Technologies of Pedestrian Detection in Vehicle-Borne Image[D]. Beijing: Beijing University of Posts and Telecommunications, 2021.
    [4]
    陈钱. 红外图像处理技术现状及发展趋势[J]. 红外技术, 2013, 35(6): 311-318. http://hwjs.nvir.cn/article/id/hwjs201306001

    CHEN Qian. The status and development trend of infrared image processing technology[J]. Infrared Technology, 2013, 35(6): 311-318. http://hwjs.nvir.cn/article/id/hwjs201306001
    [5]
    HUANG Jun, MA Yong, ZHANG Ying, et al. Infrared image enhancement algorithm based on adaptive histogram segmentation[J]. Appl. Opt, 2017, 56(35): 9686-9697. DOI: 10.1364/AO.56.009686
    [6]
    Vickers V E. Plateau Equalization algorithm for realtime display of high-quality infrared imagery [J]. Opt Eng, 1996, 35(7): 1921-1926. DOI: 10.1117/1.601006
    [7]
    LIANG Kun, MA Yong, XIE Yue, et al. A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization[J]. Infrared Phys. Technol, 2012, 55(4): 309-315. DOI: 10.1016/j.infrared.2012.03.004
    [8]
    LIU Chengwei, SUI Xiubao, KUANG Xiaodong, et al. Adaptive contrast enhancement for infrared images based on the neighborhood conditional histogram[J]. Remote Sensing, 2019, 11: 1381. Doi: 10.3390/rs11111381.
    [9]
    Zuiderveld K. Contrast limited adaptive histogram equalization[J/OL]. Graphics Gems IV, August, 1994: 474-485. https://dl.acm.org/doi/10.5555/180895.180940
    [10]
    Joung Youn K, Lee Sup K, Seung Ho H. An advanced contrast enhancement using partially overlapped sub-block histogram equalization[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2001, 11(4): 475-484. DOI: 10.1109/76.915354
    [11]
    Barash D. A fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24: 844-848. DOI: 10.1109/TPAMI.2002.1008390
    [12]
    Francesco B, Marco D and Giovanni C. New technique for the visualization of high dynamic range infrared images[J]. Optical Engineering, 2009, 48(9): 096401. DOI: 10.1117/1.3216575
    [13]
    ZUO C, CHEN Q, LIU N, et al. Display and detail enhancement for high-dynamic-range infrared images[J]. Optical Engineering, 2011, 50(12): 127401.
    [14]
    Frederic G, Cedric S, Bruno M. Real-time visualization of high-dynamic-range infrared images based on human perception characteristics - noise removal, image detail enhancement and time consistency[C]//VISAPP, 2015: 144-152.
    [15]
    汪子君, 罗渊贻, 蒋尚志, 等. 基于引导滤波的自适应红外图像增强改进算法[J]. 光谱学与光谱分析, 2020, 40(11): 3463-3467.

    WANG Zijun, LUO Yuanyi, JIANG Shangzhi, et al. An improved algorithm for adaptive infrared image enhancement based on guided filtering[J]. Spectroscopy and Spectral Analysis, 2020, 40(11): 3463-3467.
    [16]
    胡家珲, 詹伟达, 桂婷婷, 等. 基于多尺度加权引导滤波的红外图像增强方法[J]. 红外技术, 2022, 44(10): 1082-1088. http://hwjs.nvir.cn/article/id/be19ce07-80c0-43ee-85ef-7f82fc8988d9

    HU Jiahui, ZHAN Weida, GUI Tingting, et al. Infrared image enhancement method based on multiscale weighted guided filtering[J]. Infrared Technology, 2022, 44(10): 1082-1088. http://hwjs.nvir.cn/article/id/be19ce07-80c0-43ee-85ef-7f82fc8988d9
    [17]
    HE Kaiming, SUN Jian, TANG Xiao. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 35(6): 1397-1409.
    [18]
    汪伟, 许德海, 任明艺. 一种改进的红外图像自适应增强方法[J]. 红外与激光工程, 2021, 50(11): 20210086.

    WANG Wei, XU Dehai, REN Mingyi. An improved infrared image adaptive enhancement method[J]. Infrared and Laser Engineering, 2021, 50(11): 20210086.
    [19]
    LIU Ning, ZHAO Dongxue. Detail enhancement for high-dynamic-range infrared images based on guided image filter[J]. Infrared Physics & Technology, 2014, 67: 138-147.
    • Related Articles

  • Related Articles

    [1]XU Shiwen, WANG Heng, ZHANG Hua, PANG Jie. Human Fall Detection Method Based on Key Points in Infrared Images[J]. Infrared Technology , 2021, 43(10): 1003-1007.
    [2]ZHANG Zhipeng, SHAO Xuejun, PANG Qing. Research on the Key Technology of 3D Laser Inverted Scanning[J]. Infrared Technology , 2021, 43(8): 752-756.
    [3]A Method of Object Tracking Based on Feature Point Matching[J]. Infrared Technology , 2016, 38(7): 597-601.
    [4]ZHAO De-li, ZHU You-pan, LI Yan, ZENG Bang-ze, PAN Chao, LUO Lin, WU Cheng. Investigation on Infrared and Low Light Level Image Registration Algorithm Based on Point Feature and Freeman Chain Code[J]. Infrared Technology , 2015, (6): 467-471.
    [5]ZHAO De-li, ZHU You-pan, WU Cheng, LI Ze-min, ZENG Bang-ze, LUO Lin, YANG Peng-wei, WANG Bing, LI Yan. Investigation on Improved Infrared Image Registration Algorithm Based on Point Feature and Gray Feature[J]. Infrared Technology , 2014, (10): 820-826.
    [6]YU Hong-sheng, JIN Wei-qi. SIFT Key-points Self-adaptive Extraction Algorithm for Video Images[J]. Infrared Technology , 2013, (12): 768-772.
    [7]YANG Li, YANG Hua. The Key Techniques and Applications of Infrared False Target[J]. Infrared Technology , 2006, 28(9): 531-534. DOI: 10.3969/j.issn.1001-8891.2006.09.009
    [8]ZHAO Qin, ZHOU Tao, SHU Qin. Discussion of Image Registration Based on Feature Points[J]. Infrared Technology , 2006, 28(6): 327-330. DOI: 10.3969/j.issn.1001-8891.2006.06.005
    [9]Study on the Key Techniques of the Imaging Infrared Guidance for AAM[J]. Infrared Technology , 2003, 25(4): 45-48. DOI: 10.3969/j.issn.1001-8891.2003.04.011
    [10]Modification of the Infrared Point Measurement for Temperature[J]. Infrared Technology , 2002, 24(3): 49-51,55. DOI: 10.3969/j.issn.1001-8891.2002.03.013

  • Cited by

    Periodical cited type(2)

    1. 邢志坤. 基于LabVIEW的变电站移动机器人轨迹跟踪虚拟仿真系统设计. 自动化与仪表. 2024(07): 67-71 .
    2. 李辉，余大成，陈耀. 基于OWA算子和CWAA算子的变电站巡视周期优化. 广西电力. 2024(05): 50-54 .

    Other cited types(1)

Catalog

    Get Citation
    PDF
    XML
    Article views PDF downloads Cited by(3)
    Related

    Copyright © 《Infrared Technology》Editorial Office滇ICP备12000354号-3

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return