Advanced Search
中文
Volume 45 Issue 6
Jun.  2023
Turn off MathJax
Article Contents
Abstract
References
Related Articles
HE Zhibo, ZENG Xiangjin, DENG Chen, SONG Pengpeng. Infrared Image Enhancement Based on Local Entropy-Local Contrast and Dual-area Histogram Equalization[J]. Infrared Technology , 2023, 45(6): 598-604.
Citation: HE Zhibo, ZENG Xiangjin, DENG Chen, SONG Pengpeng. Infrared Image Enhancement Based on Local Entropy-Local Contrast and Dual-area Histogram Equalization[J]. Infrared Technology , 2023, 45(6): 598-604.
shu

Infrared Image Enhancement Based on Local Entropy-Local Contrast and Dual-area Histogram Equalization

  • School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China

More Information
  • Received Date: June 30, 2021
  • Revised Date: May 14, 2023
    Graphical Abstract
    • Abstract
  • We propose an infrared image enhancement algorithm based on an improved local contrast (LC) significance detection algorithm and two-area histogram equalization to improve the visual effect of an infrared image, highlight detailed information, and suppress noise. First the LC saliency detection algorithm was combined with local entropy weighting to obtain the saliency map. Then, the saliency map was adaptively segmented into foreground and background regions by the K-means algorithm. Finally, the foreground sub-histogram was equalized using a local variance-weighted distribution. The background region was enhanced using contrast-limited adaptive histogram equalization. Experimental results showed that the subjective effect of the algorithm in this study was better than the current mainstream algorithms, and the objective evaluation parameters, such as peak signal-to-noise ratio, structural similarity, and entropy, were also improved.
    • FullText(HTML)
    • References (19)
  • [1]
    史公鹏. 红外图像增强算法研究[D]. 西安: 西安电子科技大学, 2019.

    SHI Gongpeng. Research on Infrared Image Enhancement Algorithm[D]. Xi'an: Xidian University, 2019.
    [2]
    郭中原. 红外图像细节增强方法研究[D]. 重庆: 重庆邮电大学, 2017.

    GUO Zhongyuan. Research on Infrared Image Detail Enhancement Method[D]. Chongqing: Chongqing University of Posts and Telecommunications, 2017.
    [3]
    Kim Y T. Contrast enhancement using brightness preserving bi-histogram equalization[J]. IEEE Transactions on Consumer Electronics, 1997, 43(1): 1-8. DOI: 10.1109/30.580378
    [4]
    WANG Yu, CHEN Qian, ZHANG Baeomin, et al. Image enhancement based on equal area dualistic sub-image histogram equalization method[J]. IEEE Transactions on Consumer Electronics, 1999, 45(1): 68-68. DOI: 10.1109/30.754419
    [5]
    CHEN, Soong Der, A R Ramli. Minimum mean brightness error bi-histogram equalization in contrast enhancement[J]. IEEE Transactions on Consumer Electronics, 2004, 49(4): 1 310-1319.
    [6]
    LIU C, SUI X, KUANG X et al. Optimized contrast enhancement for infrared images based on global and local histogram specification[J]. Remote Sensing, 2019, 11(7): 849. DOI: 10.3390/rs11070849
    [7]
    李牧, 周瑞杰, 田哲嘉. 基于直方图的热红外图像增强方法[J]. 红外技术, 2020, 42(9): 880-885. http://hwjs.nvir.cn/article/id/hwjs202009010

    LI Mu, ZHOU Ruijie, TIAN Zhejia. Thermal infrared image enhancement method based on histogram[J]. Infrared Technology, 2020, 42(9): 880-885. http://hwjs.nvir.cn/article/id/hwjs202009010
    [8]
    WAN M, GU G, QIAN W, et al. Infrared image enhancement using adaptive histogram partition and brightness correction[J]. Remote Sensing, 2018, 10(5): 682. DOI: 10.3390/rs10050682
    [9]
    Ferzan Katırcıoğlu, Yusuf Çay, Zafer Cingiz. Infrared image enhancement model based on gravitational force and lateral inhibition networks -science direct[J]. Infrared Physics & Technology, 2019, 100: 15-27.
    [10]
    张鹏程, 何明霞, 陈硕, 等. 基于生成式对抗网络的太赫兹图像增强[J]. 红外技术, 2021, 43(4): 391-396. http://hwjs.nvir.cn/article/id/284915b0-5ceb-4117-a7af-0a91d88e09aa

    ZHANG Pengcheng, HE Mingxia, CHEN Shuo, et al. THz image enhancement based on generative confrontation network[J]. Infrared Technology, 2021, 43(4): 391-396. http://hwjs.nvir.cn/article/id/284915b0-5ceb-4117-a7af-0a91d88e09aa
    [11]
    Illarionova S, Nesteruk S, Shadrin D, et al. Mixchannel: advanced augmentation for multi spectral satellite images[J]. Remote Sensing, 2021(13): 2181.
    [12]
    景慧昀. 视觉显著性检测关键技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2014.

    JING Huiyun. Research on Key Technologies of Visual Saliency Detection[D]. Harbin: Harbin Institute of Technology, 2014.
    [13]
    YUN Z, Shah M. Visual attention detection in video sequences using spatiotemporal cues[C]//Proceedings of the 14th ACM International Conference on Multimedia, 2006: 23-27.
    [14]
    CHENG M, Mitra N J, HUANG X, et al. Global contrast based salient region detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 569-582. DOI: 10.1109/TPAMI.2014.2345401
    [15]
    张玉贵, 沈柳青, 胡海苗. 热红外视频监控下行人目标前景区域提取[J]. 北京航空航天大学学报, 2020, 46(9): 1721-1729. https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202009012.htm

    ZHANG Yugui, SHEN Liuqing, HU Haimiao. Extraction of the foreground area of the pedestrian target under thermal infrared video surveillance[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(9): 1721-1729. https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202009012.htm
    [16]
    韩少刚, 江巨浪. 基于图像分割的双直方图均衡算法[J]. 安庆师范大学学报(自然科学版), 2021, 27(1): 66-69. https://www.cnki.com.cn/Article/CJFDTOTAL-AQSX202101015.htm

    HAN Shaogang, JIANG Julang. Double histogram equalization algorithm based on image segmentation[J]. Journal of Anqing Normal University (Natural Science Edition), 2021, 27(1): 66-69. https://www.cnki.com.cn/Article/CJFDTOTAL-AQSX202101015.htm
    [17]
    杨力, 李东新. 基于遗传算法的图像阈值分割的研究[J]. 信息技术, 2015(11): 116-120. https://www.cnki.com.cn/Article/CJFDTOTAL-HDZJ201511032.htm

    YANG Li, LI Dongxin. Research on image threshold segmentation based on genetic algorithm[J]. Information Technology, 2015(11): 116-120. https://www.cnki.com.cn/Article/CJFDTOTAL-HDZJ201511032.htm
    [18]
    孙华庆. 非线性函数的通用线性近似算法和硬件实现[D]. 南京: 南京大学, 2020.

    SUN Huaqing. General Linear Approximation Algorithm and Hardware Implementation of Nonlinear Functions[D]. Nanjing: Nanjing University, 2020.
    [19]
    LIU C, SUI X, KUANG X et al. Adaptive contrast enhancement for infrared images based on the neighborhood conditional histogram[J]. Remote Sensing, 2019, 11: 1381.
    • Related Articles

  • Related Articles

    [1]WAN Xin, LIU Kun, CUI Changhao. Histogram Equalization Algorithm Based on Sobel Gradient and Its Application on Infrared Images[J]. Infrared Technology , 2024, 46(4): 452-459.
    [2]LU Quan, HUANG Lifeng, HU Mengzhu. SF6 Leakage Region Enhancement Algorithm Based on Improved HE[J]. Infrared Technology , 2024, 46(4): 437-442.
    [3]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.
    [4]ZHANG Huan, CHEN Zhisheng. Multi-scale Auto-Corrected Bi-Histogram Equalization for Infrared Image Enhancement[J]. Infrared Technology , 2023, 45(11): 1207-1215.
    [5]LIU He, ZHAO Tiancheng, LI Jiashuai, YANG Daiyong, YUAN Xiaocui, XU Zhihao. Contrast Enhancement Method of SF6 Infrared Image Based on Tri-histogram Equalization Algorithm[J]. Infrared Technology , 2023, 45(10): 1118-1125.
    [6]YAN Zhe, JIANG Li, YANG Fan, LUO Zhibin, JIA Zan, ZHANG Wei, ZHU Hongyang, CHEN Ruzao, ZHU Guangming, GUO Xiaojun, LIU Mengran. Bi-Histogram Equalization Algorithm for Infrared Image Enhancement[J]. Infrared Technology , 2022, 44(9): 944-950.
    [7]ZHU Jiayi, YANG Hongshuang, HE Wei, WANG Weinan, SHA Yizhong, HUANG Xiaojiang, XU Zhenjie. Implementation of a Histogram Equalization Algorithm Based on Image Segmentation[J]. Infrared Technology , 2022, 44(6): 587-592.
    [8]LI Mu, ZHOU Ruijie, TIAN Zhejia. A Thermal Infrared Image Enhancement Method Based on Histogram[J]. Infrared Technology , 2020, 42(9): 880-885.
    [9]JI Shu-peng, DING Xiao-qing. Morphological Filters and Wavelet-based Histogram Equalization Image Enhancement for Weak Target Detection[J]. Infrared Technology , 2003, 25(4): 32-38. DOI: 10.3969/j.issn.1001-8891.2003.04.008
    [10]A DSP+FPGA Based Real-time Histogram Equalization System of Infrared Image[J]. Infrared Technology , 2002, 24(3): 15-19. DOI: 10.3969/j.issn.1001-8891.2002.03.004

  • Cited by

    Periodical cited type(4)

    1. 朱榕，郑万波，王耀，谭春琳. 基于HE-CSR的红外与可见光图像改进融合方法. 光谱学与光谱分析. 2025(02): 558-568 .
    2. 温雅. 基于改进自适应直方图均衡化的红外图像增强算法研究. 长江信息通信. 2025(01): 87-90 .
    3. 乔逸卓，张红旗，马昕宇. 基于随机森林的复合绝缘子憎水性等级检测. 内蒙古电力技术. 2024(05): 94-100 .
    4. 王素珍，吕基岳，邓成禹，葛润东，李浩儒. 基于改进YOLOv5的钢铁表面缺陷检测算法. 国外电子测量技术. 2023(10): 43-50 .

    Other cited types(7)

Catalog

    Get Citation
    PDF
    XML
    Article views (214) PDF downloads (81) Cited by(11)
    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