Advanced Search
中文
Volume 46 Issue 2
Feb.  2024
Turn off MathJax
Article Contents
Abstract
References
Related Articles
WANG Zhen, LIU Lei. Infrared Image Enhancement for Power Equipment Based on Fusion Color Model Space[J]. Infrared Technology , 2024, 46(2): 225-232.
Citation: WANG Zhen, LIU Lei. Infrared Image Enhancement for Power Equipment Based on Fusion Color Model Space[J]. Infrared Technology , 2024, 46(2): 225-232.
shu

Infrared Image Enhancement for Power Equipment Based on Fusion Color Model Space

  • School of Electrical and Information Engineering, Anhui University of Technology, Maanshan 243000, China

More Information
  • Received Date: March 30, 2022
  • Revised Date: May 01, 2022
    Graphical Abstract
    • Abstract
  • There are numerous problems with infrared imaging using power equipment, such as dark brightness and low contrast. To solve these problems, an enhancement algorithm using a color-model space was proposed. In this method, the contrast and brightness enhancement of the image are processed in the HSV and RGB spaces, respectively. First, the high gray levels of the image are preprocessed, and the mixed filtering method is adopted to suppress the noise in the image. An enhancement function is used to improve the brightness of the image. Finally, the enhanced image is converted into the HSV space, the H, S and V component images are extracted, the gamma transform and CLAHE algorithms are used to improve the brightness of V component, and a nonlinear saturation correction function is used to process component S to improve the image contrast. Finally, the enhanced image in the HSV space is obtained by the corresponding fusion of each processing and extraction component, and is transferred back to the RGB space to obtain the final output image. Experimental results show that the proposed algorithm can significantly improve the contrast and brightness of infrared images. The average gray mean and standard deviation of the enhanced 6 groups of images were 115.94 and 78.65, respectively, which are improvements of 81.59 and 36.17 compared with the original image.
    • FullText(HTML)
    • References (17)
  • [1]
    张丽娜. 红外测温技术在变电站运维中的应用探讨[J]. 电子测试, 2021(21): 119-120. DOI: 10.3969/j.issn.1000-8519.2021.21.041

    ZHANG Lina. Application of infrared temperature measurement technology in substation operation and maintenance[J]. Electronic Test, 2021(21): 119-120. DOI: 10.3969/j.issn.1000-8519.2021.21.041
    [2]
    赵天成, 罗吕, 杨代勇, 等. 多属性融合的电力设备红外热特征数字化方法[J]. 红外技术, 2021, 43(11): 1097-1103. http://hwjs.nvir.cn/article/id/fdbced71-89e2-4d42-8252-4713304b6e1c

    ZHAO Tiancheng, LUO Lyu, YANG Daiyong, et al. A multi-attribute fusion method for digitizing infrared thermal characteristics of power equipment[J]. Infrared Technology, 2021, 43(11): 1097-1103. http://hwjs.nvir.cn/article/id/fdbced71-89e2-4d42-8252-4713304b6e1c
    [3]
    曾军, 王东杰, 范伟, 等. 基于红外热成像的电气设备组件识别研究[J]. 红外技术, 2021, 43(7): 679-687. http://hwjs.nvir.cn/article/id/58024112-8052-43d6-8a2d-dd2460dfa5e1

    ZENG Jun, WANG Dongjie, FAN Wei, et al. Research on component identification for electrical equipment based on infrared thermography[J]. Infrared Technology, 2021, 43(7): 679-687. http://hwjs.nvir.cn/article/id/58024112-8052-43d6-8a2d-dd2460dfa5e1
    [4]
    魏然然, 詹伟达, 朱德鹏, 等. 改进多尺度的Retinex红外图像增强[J]. 液晶与显示, 2021, 36(3): 465-474.

    WEI Ranran, ZHAN Weida, ZHU Depeng, et al. Improved multi-scale Retinex infrared image enhancement[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(3): 465-474.
    [5]
    程铁栋, 卢晓亮, 易其文, 等. 一种结合单尺度Retinex与引导滤波的红外图像增强方法[J]. 红外技术, 2021, 43(11): 1081-1088. http://hwjs.nvir.cn/article/id/b49a0a09-e295-40e6-9736-24a58971206e

    CHENG Tiedong, LU Xiaoliang, YI Qiwen, et al. Research on infrared image enhancement method combined with single-scale Retinex and guided image filter[J]. Infrared Technology, 2021, 43(11): 1081-1088. http://hwjs.nvir.cn/article/id/b49a0a09-e295-40e6-9736-24a58971206e
    [6]
    翟海祥, 何嘉奇, 王正家, 等. 改进Retinex与多图像融合算法用于低照度图像增强[J]. 红外技术, 2021, 43(10): 987-993. http://hwjs.nvir.cn/article/id/23500140-4bab-40b3-9bef-282f14dc105e

    ZHAI Haixiang, HE Jiaqi, WANG Zhengjia, et al. Improved Retinex and multi-image fusion algorithm for low illumination image enhancement[J]. Infrared Technology, 2021, 43(10): 987-993. http://hwjs.nvir.cn/article/id/23500140-4bab-40b3-9bef-282f14dc105e
    [7]
    徐武, 杨昊东, 汤弘毅, 等. 基于改进加权引导滤波的红外图像增强算法[J]. 激光杂志, 2022, 43(1): 101-106.

    XU Wu, YANG Haodong, TANG Hongyi, et al. Infrared image enhancement algorithm based on improved weighted guided filtering[J]. Laser Journal, 2022, 43(1): 101-106.
    [8]
    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. A thermal infrared image enhancement method based on histogram[J]. Infrared Technology, 2020, 42(9): 880-885. http://hwjs.nvir.cn/article/id/hwjs202009010
    [9]
    陈尧, 尹丽菊, 咸日常, 等. 基于NSCT和改进Pal_King算法的电力设备红外图像增强方法[J]. 计算机应用与软件, 2021, 38(11): 236-241, 287.

    CHEN Yao, YIN Liju, XIAN Richang, et al. Infrared image enhancement method for power equipment based on NSCT and improved Pal_ King algorithm[J]. Computer Applications and Software, 2021, 38(11): 236-241, 287.
    [10]
    朱颖, 王昕, 王爱平, 等. 基于MVOtsu和对数型模糊隶属度函数的电力设备NSST域红外图像增强[J]. 高压电器, 2020, 56(9): 179-185.

    ZHU Ying, WANG Xin, WANG Aiping, et al. Electrical equipment infrared image enhancement of NSST domain based on MVOtsu and log⁃type fuzzy membership function[J]. High Voltage Apparatus, 2020, 56(9): 179-185.
    [11]
    刘陈瑶, 胡梦竹, 张龙飞. 基于改进CLAHE的SF6红外图像增强[J]. 光学技术, 2021, 47(1): 107-112.

    LIU Chenyao, HU Mengzhu, ZHANG Longfei. Infrared image enhancement of SF6 based on improved CLAHE[J]. Optical Technique, 2021, 47(1): 107-112.
    [12]
    谭宇璇, 樊绍胜. 基于图像增强与深度学习的变电设备红外热像识别方法[J]. 中国电机工程学报, 2021, 41(23): 7990-7998.

    TAN Yuxuan, FAN Shaosheng. Infrared thermal image recognition of substation equipment based on image enhancement and deep learning[J]. Proceedings of the CSEE, 2021, 41(23): 7990-7998.
    [13]
    陈基顺, 肖立军, 万新宇, 等. 复杂环境下电力设备红外热图增强与分割研究[J]. 红外技术, 2018, 40(11): 1112-1118. http://hwjs.nvir.cn/article/id/hwjs201811016

    CHEN Jishun, XIAO Lijun, WAN Xinyu, et al. Research on enhancement and segmentation of power equipment infrared heat map in complex environment[J]. Infrared Technology, 2018, 40(11): 1112-1118. http://hwjs.nvir.cn/article/id/hwjs201811016
    [14]
    刘寿鑫, 龙伟, 李炎炎, 等. 基于HSV色彩空间的低照度图像增强[J]. 计算机工程与设计, 2021, 42(9): 2552-2560.

    LIU Shouxin, LONG Wei, LI Yanyan, et al. Low-light image enhancement based on HSV color space[J]. Computer Engineering and Design, 2021, 42(9): 2552-2560.
    [15]
    王利娟, 常霞, 任旺. 基于加权直方图均衡化彩色图像增强仿真[J]. 计算机仿真, 2021, 38(12): 126-131.

    WANG Lijuan, CHANG Xia, RENG Wang. Color image enhancement simulation based on weighted histogram equalization[J]. Computer Simulation, 2021, 38(12): 126-131.
    [16]
    刘智嘉, 夏寅辉, 杨德振, 等. 基于中值滤波器的红外图像噪声处理的改进方法[J]. 激光与红外, 2019, 49(3): 376-380.

    LIU Zhijia, XIA Yinhui, YANG Dezhen, et al. An improved method for infrared image noise processing based on median filter[J]. Laser & Infrared, 2019, 49(3): 376-380.
    [17]
    刘寿鑫, 龙伟, 李炎炎, 等. 融合彩色模型空间的非线性低照度图像增强[J]. 四川大学学报: 自然科学版, 2021, 58(1): 57-64.

    LIU Shouxin, LONG Wei, LI Yanyan, et al. Non-linear low-light image enhancement based on fusion color model space[J]. Journal of Sichuan University: Natural Science Edition, 2021, 58(1): 57-64.
    • Related Articles

  • Related Articles

    [1]LI Jianghui. A Method and System for Infrared Image Simulation Based on ModelSim[J]. Infrared Technology , 2024, 46(7): 802-806.
    [2]WANG Xia, ZHAO Jiabi, SUN Qiyang, JIN Weiqi. Performance Evaluation Model for Infrared Polarization Imaging System[J]. Infrared Technology , 2023, 45(5): 437-445.
    [3]KONG Derui, XIA Ming, LI Haiying, CHEN Jun, ZHAO Peng. Theoretical Analysis and Matlab Simulation of Dynamic Vibration Absorber for Single-Piston Linear Compressor[J]. Infrared Technology , 2021, 43(10): 1014-1021.
    [4]ZHANG Jingyang, YAN Limin, CHEN Zhiheng. Nighttime Fog Removal Using the Dark Point Light Source Model[J]. Infrared Technology , 2021, 43(8): 798-803.
    [5]HU Yang, CHEN Cheng, HUA Sangtun, QIU Yafeng. Thermal Calculation of Countercurrent Cooling Tower and Design of Infrared Thermal Image Temperature Control System[J]. Infrared Technology , 2021, 43(3): 225-229.
    [6]PAN Hao, MA Yi, ZHOU Fangrong, MA Yutang, QIAN Guochao, WEN Gang. Research on the Theoretical Model Between Solar-blind UV and Atmospheric Temperature during Atmospheric Transmission[J]. Infrared Technology , 2020, 42(10): 1007-1012.
    [7]HAN Kun, YAO Ze, QIAO Kai, YANG Shuning, HE Yingping. Theoretical Model of Dynamic MTF of Low-Light-Level ICCD[J]. Infrared Technology , 2020, 42(3): 294-299.
    [8]SUN Jianning, SI Shuguang, WANG Xingchao, JIN Muchun, LI Dong, REN Ling, HOU Wei, ZHAO Min, GU Ying, QIAO Fangjian, ZHANG Haoda, CAO Yiqi. Preparation Method of K2CsSb Photocathode Using the Reflectance Theory Model[J]. Infrared Technology , 2017, 39(12): 1087-1091.
    [9]ZHANG Yao-jun, WU Gui-ling, LI Lei. Fusion for Infrared and Visible Light Images Based on Shearlet Transform and Quantum Theory Model[J]. Infrared Technology , 2015, (5): 418-423.
    [10]Theoretic Module of Uncooled IR Detector Performance Improvement[J]. Infrared Technology , 2002, 24(4): 31-34. DOI: 10.3969/j.issn.1001-8891.2002.04.009

  • Cited by

    Periodical cited type(1)

    1. 邱祥彪，杨晓明，孙建宁，王健，丛晓庆，金戈，曾进能，张正君，潘凯，陈晓倩. 高空间分辨微通道板现状及发展. 红外技术. 2024(04): 460-466 . 本站查看

    Other cited types(0)

Catalog

    Get Citation
    PDF
    XML
    Article views (119) PDF downloads (28) Cited by(1)
    Related

    Copyright © 《Infrared Technology》Editorial Office京ICP备000000000号-1

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

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return