Mountain shadow removal for high-resolution aerial optical remote sensing images

doi:10.13474/j.cnki.11-2246.2023.0323

Abstract

Abstract: Shadow is a serious interference factor for high-resolution aerial imagery in mountainous areas. Removing mountain shadow can help improve the accuracy and effectiveness of applications, such as real-life 3D construction, forestry investigation, change detection and more. In this paper, the mountain shadow index (MSI) of high-resolution aerial remote sensing image is constructed, and a shadow removal method based on color migration and color equalization is proposed. The experiment is conducted with 0.2 m aerial imagery covering mountainous areas, the results show that MSI and threshold segmentation method can effectively detect the mountain shadow of aerial imagery, and the shadow removal method combining objectified color migration and neighborhood based nonlinear color balance can effectively eliminate mountain shadow, and can also restore texture detail in the shadow area, and make the color more suitable for non-shadow areas, so as to achieve a more balanced effect of the overall color of the image. Statistically analyzing the statistical indicators before and after shadow removal, with the removal of the shadow, the average value and standard deviation of each band increased significantly, indicating that the brightness of the shadow area is improved and the color level is richer.

Key words: aerial remote sensing, high-resolution optical images, mountain shadow, detection and compensation, color processing

CLC Number:

P237

GUO Wei, LU Wanyun, DENG Tingqi, HUANG Guodong, YOU Wenyu, YANG Rongxin, YU Han, DONG Shouyin, JIANG Rui. Mountain shadow removal for high-resolution aerial optical remote sensing images[J]. Bulletin of Surveying and Mapping, 2023, 0(11): 30-35,47.

References

[1] 刘健,许章华,余坤勇,等. 山地丘陵区遥感影像阴影检测与去除方法[J]. 农业机械学报,2013,44(10): 238-241.
[2] 杨俊,赵忠明,杨健. 一种高分辨率遥感影像阴影去除方法[J]. 武汉大学学报(信息科学版),2008,33(1): 17-20.
[3] PONS X,PADRÓ J C. An empirical approach on shadow reduction of UAV imagery in forests[C]//Proceedings of 2019 IEEE International Geoscience and Remote Sensing Symposium. Yokohama: IEEE,2019: 2463-2466.
[4] 林亚斌,贾贵刚,李莲. 高分遥感影像阴影检测与消除方法[J]. 测绘与空间地理信息,2014,37(8): 119-121.
[5] 梁永侦,潘斌,郭小明,等. 基于LAB颜色空间的图像阴影检测与去除方法[J]. 计算机与现代化,2019(10): 88-93.
[6] 伍燚垚,冯德俊,瑚敏君,等. 基于航空影像的建筑物阴影提取方法研究[J]. 地理信息世界,2019,26(6): 44-48.
[7] 罗艳,辛俊伟,夏元平. 一种改进的多光谱遥感影像阴影检测方法[J]. 测绘科学,2020,45(12): 102-107.
[8] 马皇特. 基于无人机航拍图像的阴影分割与消除[D]. 西安: 长安大学,2019.
[9]刘紫君,邱利军,张波,等. 多光谱遥感影像阴影提取[J]. 测绘与空间地理信息,2017,40(6): 77-79.
[10] 曾敬文,王学文,侯文广,等. 连续局部阈值分割的阴影检测方法[J]. 测绘科学,2016,41(11): 93-97.
[11] RAU J,CHEN Naiyu,CHEN L C. True orthophoto generation of built-up areas using multi-view images[J]. Photogrammetric Engineering and Remote Sensing,2002,68: 581-588.
[12] RAHMAN M M,MCDERMID G J,MCKEEMAN T,et al. A workflow to minimize shadows in UAV-based orthomosaics[J]. Journal of Unmanned Vehicle Systems,2019,7(2): 107-117.
[13] STOREY E A,STOW D A,PLUMMER M J. Normalizing shadows in multi-temporal aerial frame imagery using relative radiometric adjustments to support near-real-time change detection[J]. GIScience & Remote Sensing,2019,56(1): 22-42.
[14] REINHARD E,ADHIKHMIN M,GOOCH B,et al. Color transfer between images[J]. IEEE Computer Graphics and Applications,2001,21(5): 34-41.
[15] WU Qi,ZHANG Wende,VIJAYA KUMAR B V K. Strong shadow removal via patch-based shadow edge detection[C]//Proceedings of 2012 IEEE International Conference on Robotics and Automation. Saint Paul: IEEE,2012: 2177-2182.
[16] LI Y,GONG P,SASAGAWA T. Integrated shadow removal based on photogrammetry and image analysis[J]. International Journal of Remote Sensing,2005,26(18): 3911-3929.
[17] ZHOU Tingting,FU Haoyang. Shadow detection and removal from buildings in UAV data[C]//Proceedings of 2018 Frontiers in Optics/Laser Science. Washington,DC: OSA,2018.
[18] 董胜光,秦建新,郭云开. 一种高分辨率遥感影像阴影补偿方法[J]. 测绘科学,2018,43(11): 118-124.
[19] 武明虎,宋冉冉,刘敏. 结合HSV与纹理特征的视频阴影消除算法[J]. 中国图象图形学报,2017,22(10): 1373-1380.
[20] 金朝丹. 科技躬耕走出强农之路[N]. 温州日报,2021-09-28(4).
[21] TAO L,ASARI V.An integrated neighborhood dependent approach for nonlinear enhancement of color images[C]//Proceedings of 2004 International Conference on Information Technology: Coding and Computing. Las Vegas: IEEE,2004: 138-139.