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Volume 44 Issue 9
Sep.  2022
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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.
Citation: 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.
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Bi-Histogram Equalization Algorithm for Infrared Image Enhancement

  • Kunming Institute of Physics, Kunming 650223, China

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  • Received Date: December 28, 2021
  • Revised Date: February 08, 2022
    Graphical Abstract
    • Abstract
  • A modified bi-histogram equalization algorithm is proposed to suppress gray saturation and loss of local details caused by global histogram equalization. First, the background and foreground of the image are segmented, and a modified k-means clustering algorithm based on the local minimum of the histogram is proposed to determine the ideal segmentation threshold of the image. Then, histogram equalization is performed for the segmented sub-graphs. The algorithm is verified by experiments; the results for the experiment show that, compared with those from global histogram equalization, the peak signal to noise ratio and structural similarity are improved by approximately 16.425% and 14.85%, respectively. Simultaneously, through subjective evaluation, the algorithm based on histogram local minimum and modified k-means can effectively suppress the gray saturation and detail loss caused by GHE.
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    • References (22)
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