LIU Zhengnan, LIU Chunjing. Image Enhancement Algorithm Based on Texture Prior and Color Clustering[J]. Infrared Technology , 2023, 45(9): 932-940.
Citation: LIU Zhengnan, LIU Chunjing. Image Enhancement Algorithm Based on Texture Prior and Color Clustering[J]. Infrared Technology , 2023, 45(9): 932-940.

Image Enhancement Algorithm Based on Texture Prior and Color Clustering

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  • Received Date: January 02, 2023
  • Revised Date: March 08, 2023
  • To address the problems of traditional multiscale retinex with color restoration (MSRCR), such as texture information weakening, partial information loss, and poor enhancement effects, an image enhancement algorithm based on texture priors and color clustering is proposed. First, prior to image enhancement, texture information is extracted for further processing. Second, considering the uneven illumination distribution, a color-clustering algorithm is proposed for image segmentation enhancement. In addition, for logarithmic domain mapping, a mapping scheme based on mean square value and mean square error is proposed based on block processing. Finally, in evaluating the enhancement algorithm, information entropy and natural statistics of the image are used to evaluate the effectiveness of the enhanced image. The experimental results show that the average entropy of the proposed method reached 7.4934 and the average of natural statistical properties reached 4.0903. The algorithm effectively enhances the details of the image, makes the image more natural, and further improves image quality.
  • [1]
    孙晓斐, 祁卓, 孙王倩, 等. 基于特征融合的红外图像增强算法[J]. 光学技术, 2022, 48(2): 250-256. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJS202202021.htm

    SUN Xiaofei, QI Zhuo, SUN Wangqian, et al. Infrared image enhancement algorithm based on feature fusion[J]. Optical Technique, 2022, 48(2): 250-256. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJS202202021.htm
    [2]
    潘晓英, 魏苗, 王昊, 等. 多尺度融合残差编解码器的低照度图像增强方法[J]. 计算机辅助设计与图形学学报, 2022, 34(1): 104-112. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJF202201012.htm

    PAN Xiaoying, WEI Miao, WANG Hao, et al. A multi-scale fusion residual encoder-decoder approach for low illumination image enhancement[J]. Journal of Computer-Aided Design & Computer Graphics, 2022, 34(1): 104-112. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJF202201012.htm
    [3]
    王知音, 张二虎, 石争浩, 等. 零参考样本下的逆光图像深度学习增强方法[J]. 中国图象图形学报, 2022, 27(5): 1589-1603. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB202205016.htm

    WANG Zhiyin, ZHANG Erhu, SHI Zhenghao, et al. Deep learning based backlight image enhancement method derived of zero-reference samples[J]. Journal of Image and Graphics, 2022, 27(5): 1589-1603. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB202205016.htm
    [4]
    徐少平, 林珍玉, 张贵珍, 等. 采用深度学习与图像融合混合实现策略的低照度图像增强算法[J]. 电子学报, 2021, 49(1): 72-76. https://www.cnki.com.cn/Article/CJFDTOTAL-DZXU202101010.htm

    XU Shaoping, LIN Zhenyu, ZHANG Guizhen, et al. A low-light image enhancement algorithm using the hybrid strategy of deep learning and image fusion[J]. Acta Electronica Sinica, 2021, 49(1): 72-76. https://www.cnki.com.cn/Article/CJFDTOTAL-DZXU202101010.htm
    [5]
    闫哲, 蒋砾, 杨帆, 等. 基于双直方图均衡算法的红外图像增强[J]. 红外技术, 2022, 44(9): 944-950. http://hwjs.nvir.cn/article/id/fd34432d-340f-429b-b2ae-790b2c85b4b0

    YAN Zhe, JIANG Shuo, YANG Fan, et al. Bi-Histogram equalization algorithm for infrared image enhancement[J]. Infrared Technology, 2022, 44(9): 944-950. http://hwjs.nvir.cn/article/id/fd34432d-340f-429b-b2ae-790b2c85b4b0
    [6]
    郭永坤, 朱彦陈, 刘莉萍, 等. 空频域图像增强方法研究综述[J]. 计算机工程与应用, 2022, 58(11): 23-32. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202211003.htm

    GUO Yongkun, ZHU Yanchen, LIU Liping, et al. Research review of space-frequency domain image enhancement methods[J]. Computer Engineering and Applications, 2022, 58(11): 23-32. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202211003.htm
    [7]
    Land E H. The retinex theory of color vision[J]. Scientific American, 1978, 237(6): 108-128.
    [8]
    Land E, McCann J. Lightness and Retinex theory[J]. Journal of the Optical Society of America, 1971, 61: 1-11.
    [9]
    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
    [10]
    钱玉洋, 魏巍, 陈灯. 基于改进MSR的锂电池X射线图像增强算法[J]. 电子测量技术, 2022, 45(9): 113-120. https://www.cnki.com.cn/Article/CJFDTOTAL-DZCL202209017.htm

    QIAN Yuyang, WEI Wei, CHEN Deng. X- ray image enhancement algorithm of lithium battery based on improved MSR[J]. Electronic Measurement Technology, 2022, 45(9): 113-120. https://www.cnki.com.cn/Article/CJFDTOTAL-DZCL202209017.htm
    [11]
    郝蕊洁, 万小红. 改进多尺度Retinex的激光图像超分辨增强[J]. 激光杂志, 2022, 43(9): 124-128. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202209023.htm

    HAO Ruijie, WAN Xiaohong. Laser image super - resolution enhancement based on improved multi - scale Retinex[J]. Laser Journal, 2022, 43(9): 124-128. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202209023.htm
    [12]
    CAI B, XU X, GUO K, et al. A joint intrinsic-extrinsic prior model for Retinex[C]//IEEE International Conference on Computer Vision (ICCV), 2017: 4000-4009.
    [13]
    云海姣, 夏洋. 结合自适应Gamma变换和MSRCR算法的低光照图像增强方法[J]. 中国科技论文, 2022, 17(11): 1245-1253. https://www.cnki.com.cn/Article/CJFDTOTAL-ZKZX202211011.htm

    YUN Haijiao, XIA Yang. Low-light image enhancement method combined with adaptive Gamma transformation and MSRCR algorithm[J]. China Science Paper, 2022, 17(11): 1245-1253. https://www.cnki.com.cn/Article/CJFDTOTAL-ZKZX202211011.htm
    [14]
    XU Jun, HOU Yingkun, REN Dongwei, et al. STAR: a structure and texture aware Retinex model[J]. IEEE transactions on image processing: a publication of the IEEE Signal Processing Society, 2020, 29: 5022-5037.
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