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自然资源遥感  2024, Vol. 36 Issue (2): 70-79    DOI: 10.6046/zrzyyg.2023010
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
面向海岛海岸带区域的高分遥感影像智能化色彩增强方法
赵彬如1(), 牛思文2, 王力彦1, 杨晓彤1, 焦红波1, 王子珂1()
1.国家海洋信息中心,天津 300012
2.武汉大学遥感信息工程学院,武汉 430000
An intelligent color enhancement method for high-resolution remote sensing images of the coastal zone of an island
ZHAO Binru1(), NIU Siwen2, WANG Liyan1, YANG Xiaotong1, JIAO Hongbo1, WANG Zike1()
1. National Marine Data and Information Service, Tianjin 300012, China
2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430000, China
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摘要 

原始高空间分辨率海岛海岸带遥感影像往往存在影像灰暗、偏色、地物信息较难辨识的现象。为及时获取清晰、信息丰富、反差适中、亮度均匀的海岛礁遥感影像,满足日益强烈的海岛海岸带地理信息保障需求,针对海岛海岸带高空间分辨率遥感影像,该文提出一种深度学习结合改进直方图匹配的智能化调色方法。首先,进行数据重采样与自适应分块获取抽稀影像; 其次,应用MBLLEN网络对抽稀影像进行真彩色增强; 最后,采用改进直方图匹配的方法对原始影像进行色彩映射,最终得到符合人眼视觉、色彩一致、细节丰富的遥感影像。采用主客观相结合的方式综合评价调色效果,结果表明: 相较于Retinex,HE和MASK等常用调色方法,该文算法结果更符合人眼视觉、色彩一致、细节丰富,可有效改善海岛海岸带高空间分辨率遥感影像视觉效果,较好地保留原始地物的细节信息,大幅提升调色效率。

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赵彬如
牛思文
王力彦
杨晓彤
焦红波
王子珂
关键词 海岛海岸带遥感影像MBLLEN直方图匹配色彩映射    
Abstract

The original high-spatial-resolution remote sensing images of coastal zones of islands often exhibit a gray tone, color cast, and indistinguishable surface feature information. In response to the increasing demand for geographic information security of coastal zones of islands, this study aims to obtain timely clear remote sensing images with rich information, moderate contrast, and uniform brightness for island reefs. Hence, it proposed an intelligent color enhancement method by combining deep learning with improved histogram matching for high-spatial-resolution remote sensing images of coastal zones of islands. First, data resampling and adaptive chunking were performed to obtain thinned images. Then, the MBLLEN network was applied to enhance the thinned images with true color. Finally, an improved histogram matching method was employed for color mapping of original images, obtaining remote sensing images with consistent colors and rich details conforming to human vision. The color-matching effects of these obtained remote sensing images were evaluated using both subjective and objective methods. The results show that compared to other commonly used color-matching methods like Retinex, HE, and MASK, the method proposed in this study yielded more satisfactory results characterized by consistent colors and rich details conforming to human vision. Therefore, the proposed method can effectively improve the visual effects of high-spatial-resolution remote sensing images of coastal zones of islands, effectively retain the details of original surface features, and significantly enhance color-matching efficiency.

Key wordsremote sensing image of the coastal zone of an island    MBLLEN    histogram matching    color mapping
收稿日期: 2023-01-16      出版日期: 2024-06-14
ZTFLH:  TP79  
基金资助:国家自然科学基金青年基金项目“面向海山底栖生境图的多波束地形因子精确提取方法研究”(42206200)
通讯作者: 王子珂(1994-),男,硕士,助理工程师,研究方向为岛礁遥感、水色遥感。Email: kzwhisky@foxmail.com
作者简介: 赵彬如(1993-),女,硕士,助理工程师,研究方向为海岸带岛礁遥感、极地遥感。Email: whu_zbr0409@163.com
引用本文:   
赵彬如, 牛思文, 王力彦, 杨晓彤, 焦红波, 王子珂. 面向海岛海岸带区域的高分遥感影像智能化色彩增强方法[J]. 自然资源遥感, 2024, 36(2): 70-79.
ZHAO Binru, NIU Siwen, WANG Liyan, YANG Xiaotong, JIAO Hongbo, WANG Zike. An intelligent color enhancement method for high-resolution remote sensing images of the coastal zone of an island. Remote Sensing for Natural Resources, 2024, 36(2): 70-79.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023010      或      https://www.gtzyyg.com/CN/Y2024/V36/I2/70
Fig.1  研究区位置
Fig.2  总技术流程
Fig.3  影像重采样及自适应分块
Fig.4  MBLLEN网络结构
Fig.5  部分最小感兴趣地物色彩单元
Fig.6  抽稀影像真彩色增强效果对比
Fig.7  高分辨率影像调色前后结果对比
Fig.8-1  区域1色阶补偿前后影像及直方图
Fig.8-2  区域1色阶补偿前后影像及直方图
Tab.1  不同方法调色结果对比
影像名 方法 均值 标准差 色彩丰富度 变异系数 信息熵 峰值信噪比
影像1 原始 31.921 27.800 5.000 87.100 6.017
Retinex 74.010 44.540 13.411 60.193 7.331 16.241
HE 132.320 66.883 20.112 50.541 7.191 7.972
Mask 38.792 23.684 8.422 61.042 5.773 24.013
本文算法 88.050 56.421 25.615 64.086 7.434 12.993
影像2 原始 27.700 27.429 5.212 99.038 5.611
Retinex 60.122 42.781 10.313 71.152 7.722 18.822
HE 121.603 61.734 19.153 50.763 7.321 8.650
Mask 22.592 19.681 6.930 87.114 6.171 25.530
本文算法 82.638 62.723 26.338 75.900 7.827 13.830
影像3 原始 30.262 22.010 1.700 72.720 5.770
Retinex 61.795 41.362 11.202 66.932 7.520 16.330
HE 122.326 60.911 20.411 49.792 7.190 8.011
Mask 23.202 15.646 6.353 67.411 5.382 25.582
本文算法 85.531 58.442 23.370 68.333 7.400 12.892
影像4 原始 34.710 28.105 11.511 80.963 6.143
Retinex 77.172 45.872 14.882 59.444 7.331 18.420
HE 142.331 68.830 23.122 48.362 7.691 7.990
Mask 41.162 23.090 8.821 56.102 5.653 26.612
本文算法 90.351 63.892 27.270 70.713 7.773 12.671
拼合后影像 原始 30.216 26.383 6.881 79.665 5.897
Retinex 68.673 43.009 12.177 65.110 7.430 17.071
HE 136.377 64.113 20.091 49.989 7.200 8.003
Mask 35.535 20.587 7.689 72.213 5.962 25.451
本文算法 86.721 60.080 25.556 68.839 7.509 13.156
Tab.2  不同算法调色结果评价指标统计
[1] 李晓敏, 张杰, 马毅, 等. 粤西海岛海岸带典型地类SPOT-5影像解译标志[J]. 海洋通报, 2011, 30(4):447-450,455.
Li X M, Zhang J, Ma Y et al. Interpretation marks of SPOT-5 image on typical target types of islands and coastal zone in western Guangdong[J]. Marine Science Bulletin, 2011, 30(4):447-450,455.
[2] 余磊. 光学遥感卫星色彩一致性合成影像生成关键技术研究[D]. 武汉: 武汉大学, 2017.
Yu L. Key technology on color balancing for creation of color consistency synthetic products with optical remote sensing imagery[D]. Wuhan: Wuhan University, 2017.
[3] 武彬, 江家宝. 基于链接突触计算网络的遥感图像对比度增强算法[J]. 计算机应用与软件, 2020, 37(4):214-219.
Wu B, Jiang J B. Contrast enhancement algorithm of remote sensing images based on linking synaptic computation network[J]. Computer Applications and Software, 2020, 37(4):214-219.
[4] 张星铭, 孙文邦, 岳广. 基于色彩恒常理论的多光谱图像真彩色复原技术[J]. 兵器装备工程学报, 2020, 41(11):248-256.
Zhang X M, Sun W B, Yue G. True color restoration of multispectral image based on color constancy[J]. Journal of Ordnance Equipment Engineering, 2020, 41(11):248-256.
[5] 元建胜. 面向大规模02C卫星影像的色彩处理技术[J]. 海洋测绘, 2017, 37(1):66-70.
Yuan J S. Color consistency processing technology of large-scale 02C satellite images[J]. Hydrographic Surveying and Charting, 2017, 37(1):66-70.
[6] 韩宇韬. 数字正射影像镶嵌中色彩一致性处理的若干问题研究[D]. 武汉: 武汉大学, 2014.
Han Y T. Research on key technology of color consistency processing for digtial ortho map mosaicing[D]. Wuhan: Wuhan University, 2014.
[7] 张荞, 张艳梅, 蒙印. 基于直方图匹配的多源遥感影像匀色研究[J]. 地理空间信息, 2020, 18(12):54-57,7.
Zhang Q, Zhang Y M, Meng Y. Research on color uniforming for multi-source remote sensing images based on histogram matching method[J]. Geospatial Information, 2020, 18(12):54-57,7.
[8] Rizzi A, Gatta C, Marini D. From Retinex to automatic color equalization:Issues in developing a new algorithm for unsupervised color equalization[J]. Journal of Electronic Imaging, 2004, 13(1):75-84.
[9] 袁修孝, 韩宇韬, 方毅. 改进的航摄影像Mask匀光算法[J]. 遥感学报, 2014, 18(3):630-641.
Yuan X X, Han Y T, Fang Y. Improved Mask dodging algorithm for aerial imagery[J]. Journal of Remote Sensing, 2014, 18(3):630-641.
[10] 曹彬才, 朱宝山, 李润生, 等. 用于单幅影像匀光的Wallis算法[J]. 测绘科学技术学报, 2012, 29(5):373-377.
Cao B C, Zhu B S, Li R S, et al. Wallis algorithm for single image dodging[J]. Journal of Geomatics Science and Technology, 2012, 29(5):373-377.
[11] 李德仁, 王密, 潘俊. 光学遥感影像的自动匀光处理及应用[J]. 武汉大学学报(信息科学版), 2006, 31(9):753-756.
Li D R, Wang M, Pan J. Auto-dodging processing and its application for optical RS images[J]. Geomatics and Information Science of Wuhan University, 2006, 31(9):753-756.
[12] 王密, 潘俊. 一种数字航空影像的匀光方法[J]. 中国图象图形学报, 2004, 9(6):744-748.
Wang M, Pan J. A method of removing the uneven illumination for digital aerial image[J]. Journal of Image and Graphics, 2004, 9(6):744-748.
[13] Orsini G, Ramponi G, Carrai P, et al. A modified retinex for image contrast enhancement and dynamics control[C]// International Conference on Image Processing.IEEE, 2003:393-398.
[14] Lam E Y. Combining gray world and retinex theory for automatic white balance in digital photography[C]// Proceedings of the Ninth International Symposium on Consumer Electronics,2005.(ISCE 2005).IEEE, 2005:134-139.
[15] Seow M J, Asari V K. Ratio rule and homomorphic filter for enhancement of digital colour image[J]. Neurocomputing, 2006, 69(7/8/9):954-958.
[16] Hsia S C, Chen M H, Chen Y M. A cost-effective line-based light-balancing technique using adaptive processing[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2006, 15(9):2719-2729.
[17] 李国. 基于遗传算法的遥感影像增强技术研究[D]. 郑州: 解放军信息工程大学, 2012.
Li G. The study of remote sensing image enhancement based on genetic algorithms[D]. Zhengzhou: Information Engineering University, 2012.
[18] Li Q Q, Lu Y, Hu S B, et al. Review of remotely sensed geoenvironmental monitoring of coastal zones[J]. Journal of Remote Sensing, 2016, 20(5):1216-1229.
[19] Lyu F F, Lu F, Wu J H, et al. MBLLEN:Low-light image/video enhancement using CNNs[C]// British MachineVision Conference.IEEE, 2018:.220-233.
[20] 陈建乐, 刘济林, 叶建洪, 等. 多视点视频中基于局部直方图匹配的亮度和色差校正[J]. 中国图象图形学报, 2007, 12(11):1992-1999.
Chen J L, Liu J L, Ye J H, et al. Luminance and chrominance correction for multi-view video using overlapped local histogram matching[J]. Journal of Image and Graphics, 2007, 12(11):1992-1999.
[21] 周妍, 李庆武, 霍冠英. 基于非下采样Contourlet变换系数直方图匹配的自适应图像增强[J]. 光学精密工程, 2014, 22(8):2214-2222.
Zhou Y, Li Q W, Huo G Y. Adaptive image enhancement based on NSCT coefficient histogram matching[J]. Optics and Precision Engineering, 2014, 22(8):2214-2222.
[22] 孙立辉, 张竟雄. 基于高斯平滑直方图匹配的图像间匀光算法[J]. 信息与电脑(理论版), 2021, 33(21):45-47.
Sun L H, Zhang J X. Uniform light between images based on Gaussian smooth histogram matching[J]. China Computer and Communication, 2021, 33(21):45-47.
[23] 丁春秋. 基于混合直方图匹配的多相机色彩校正[D]. 南京: 南京大学, 2021.
Ding C Q. Multi-camera color correction via hybrid histogram matching[D]. Nanjing: Nanjing University, 2021.
[24] 卢其剑. 基于区域网平差的遥感影像色彩均衡算法研究[D]. 南昌: 东华理工大学, 2020.
Lu Q J. Research on remote sensing image color equalization method based on block adjustment[D]. Nanchang: East China University of Technology, 2020.
[25] Hasler D, Suesstrunk S E. Measuring colorfulness in natural images[J]. Hunman Vision and Electronic Imaging, 2003, 6(17):87-96.
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