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Volume 30 Issue 2
Apr  2022
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Article Navigation >  Journal of Unmanned Undersea Systems  > 2022  >  30(2): 204-208,230
LI Qiu-ju, XU Hai-ping, GOU Chun. Pseudo-color Enhancement Methods and Quality Evaluation of Sonar Image Based on the CIELab Color Space and HIS Color Space[J]. Journal of Unmanned Undersea Systems, 2022, 30(2): 204-208,230. doi: 10.11993/j.issn.2096-3920.2022.02.010
Citation: LI Qiu-ju, XU Hai-ping, GOU Chun. Pseudo-color Enhancement Methods and Quality Evaluation of Sonar Image Based on the CIELab Color Space and HIS Color Space[J]. Journal of Unmanned Undersea Systems, 2022, 30(2): 204-208,230. doi: 10.11993/j.issn.2096-3920.2022.02.010
shu

Pseudo-color Enhancement Methods and Quality Evaluation of Sonar Image Based on the CIELab Color Space and HIS Color Space

doi: 10.11993/j.issn.2096-3920.2022.02.010

  • Kunming Branch of the 705 Research Institute, China State Shipbuilding Corporation Limited, Kunming 650106, China

  • Received Date: 2021-04-25
    Available Online: 2022-07-16
    Abstract
  • At present, pseudo-color enhancement methods for sonar images are based only on the RGB and HSV color spaces. To this end, two novel sonar image pseudo-color enhancement methods based on the CIELab color space and HIS color space are introduced in this study. The quality of the enhanced images obtained by the two methods was evaluated. First, a novel pseudo-color real-time enhancement method based on the CIELab color space is proposed. The enhanced image obtained using this method was clearer and had richer levels. Second, combined with the Otsu method and according to the grayscale distribution characteristics of sonar images, a novel adaptable pseudo-color enhancement method based on the HIS color space is introduced. This method has strong adaptability, and the enhanced image obtained using this method is information-rich. Finally, two objective evaluation methods were used to verify the effectiveness of the enhancement methods in conjunction with the subjective evaluation method.

     

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    • References(16)
  • [1]
    刘维,刘纪元,黄海宁,等.声纳图像伪彩色处理的调色板连续编码方法[J].系统仿真学报, 2005, 17(7):1724-1731.

    Liu Wei, Liu Ji-yuan, Huang Hai-ning, et al. Palette's Continuous Coding Method for Sonar Image Pseudo-color Processing[J]. System Simulation, 2005, 17(7):1724-1731.
    [2]
    赵向文,靳国旺,许竞轩,等.基于多阈值大津法直方图分割的SAR数据伪彩色量化方法[J].测绘科学技术学报, 2012, 29(6):445-449.

    Zhao Xiang-wen, Jin Guo-wang, Xu Jing-xuan, et al. Pesudo-Color Quantization of SAR Data Based on Multi-Threshold Otsu Method of Histogram Segmentation[J]. Journal of Geomatics Science and Technology, 2012, 29(6):445-449.
    [3]
    Welsh T, Ashikhmin M, Mueller K. Transferring Color to Grayscal Images[J]. ACM Transactions on Graphics, 2002, 21(3):277-280.
    [4]
    曹茂永,郁道银.基于感知颜色空间的灰度图像伪彩色编码[J].光学技术, 2002, 28(4):61-63.

    Cao Mao-yong, Yu Dao-yin. Pseudocolor Coding of Gray Image Based on Perceptual Color[J]. Optical Technique, 2002, 28(4):61-63.
    [5]
    Toet A. Colorizing Single Band Intensified Nightvision images[J]. Displays, 2005, 26(1):15-21.
    [6]
    熊平波.侧扫声呐中的伪彩色图像处理研究[D].昆明:昆明理工大学, 2019.
    [7]
    陈亚欣,武文波.基于Robrt梯度与HIS色彩空间的SAR图像伪彩色编码[J].测绘与空间地理信息, 2017, 40(4):85-88.

    Chen Ya-xin, Wu Wen-bo. Pseudo-color Coding of SAR Images Based on Roberts Gradient and HIS Color Space[J]. Geomatics&Spatial Information Technology, 2017, 40(4):85-88.
    [8]
    朱进,李力,金伟其,等.低照度夜视成像的自然感彩色化及增强方法[J].光子学报, 2018, 47(4):1-10.

    Zhu Jin, Li Li, Jin Wei-qi, et al. Natural-appearance Colorization and Enhancement for the Low-light-level Night Vision Imaging[J]. Acta Photonica Ainica, 2018, 47(4):1-10.
    [9]
    张济博,潘国富,蒋维杰,等.侧扫声纳图像伪彩色增强研究[J].声学技术, 2015, 34(4):114-117.

    Zhang Ji-bo, Pan Guo-fu, Jiang Wei-jie, et al. Pseudo-color Enhancement for Side Scan Sonar Image[J]. Technical Acoustics, 2015, 34(4):114-117.
    [10]
    赵军辉,吴玉峰,胡坤融,等.基于Lab色彩空间和色调映射的彩色图像增强算法[J].计算机科学, 2018, 45(2):114-117.

    Zhao Jun-hui, Wu Yu-feng, Hu Kun-rong, et al. Color Image Enhancement Algorithm Based on Lab Color Space and Tone Mapping[J]. Computer Science, 2018, 45(2):114-117.
    [11]
    余磊,靳国旺,徐青,等.基于非线性编码和lαβ变换的SAR图像伪彩色增强[J].测绘科学技术学报, 2012, 29(3):192-195.

    Yu Lei, Jin Guo-wang, Xu Qing, et al. SAR Image Pseudo-Color Enhancement Based on Nonlinear Coding and lαβ Transformation[J]. Journal of Geomatics Science and Technology, 2012, 29(3):192-195.
    [12]
    卢红阳,刘且根,熊娇娇,等.基于最大加权投影求解的彩色图像灰度化对比度保留的算法[J].自动化学报, 2017, 43(5):843-853.

    Lu Hong-yang, Liu Qie-gen, Xiong Jiao-jiao, et al. Maximum Weighted Projection Solver for Contrast Preserving Decolorization[J]. Acta Automatica Sinica, 2017, 43(5):843-853.
    [13]
    曹丽琴,商永星,刘婷婷,等.局部自适应的灰度图像彩色化[J].中国图像图形学报, 2019, 24(8):1249-1257.

    Cao Li-qin, Shang Yong-xing, Liu Ting-ting, et al. Novel Image Colorrization of Adaptive Weighted Average Filter[J]. Journal of Image and Graphics, 2019, 24(8):1249-1257.
    [14]
    李晓冰.一种基于HSI空间的红外测量图像伪彩色编码方法[J].测试技术学报, 2012, 26(4):343-347.

    Li Xiao-bing. A Pseudo-Color Coding Method for HIS Space Based on Infrared Measurement Image[J]. Journal of Test and Measurement Technology, 2012, 26(4):343-347.
    [15]
    Sheng Z, Jiang X Y, Zhen W. Pseudo-Color Coding with Phase-Modulated Image Density[J]. Advanced Materials Research, 2012, 403-408:1618-1621.
    [16]
    王静娇.成像声纳数据实时传输与显示控制技术研究[D].南京:南京航空航天大学, 2013.
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