基于最优路径的无人机影像辐射区域网平差

doi:10.13474/j.cnki.11-2246.2023.0009

摘要/Abstract

摘要： 无人机遥感能够提供高时空分辨率的影像数据,拥有广泛的应用前景。辐射校正将传感器记录的数据转化为地表反射率,是无人机数据定量化应用的前提。然而无人机数据易受光照等因素的影响,导致影像间存在不同程度的辐射差异,为多张无人机影像的辐射校正带来困难。基于影像间重叠区域的信息,辐射区域网平差能够获得全局最优的辐射校正参数,降低影像间的辐射差异,因此在实现影像的辐射校正方面具有巨大潜力。但大量待求解未知参数降低了辐射校正模型的求解效率,特别是在数据量急剧增加时,该问题更为突出。基于影像重叠区辐射信息建立的最优路径很好地考虑了影像间的辐射转化关系,可有效控制误差累计,为减少辐射区域网平差中未知参数的数量提供了一种思路。因此,本文将最优路径与辐射区域网平差相结合,以降低待求解参数的数量,在保证辐射校正精度的同时提高辐射校正模型求解效率,进而提升辐射区域网平差在大数据集上的应用潜力。

关键词: 无人机, 辐射校正, 最优路径, 辐射区域网平差

Abstract: Unmanned aerial vehicle (UAV) remote sensing can provide imagery data with high spatio-temporal resolution, and has a wide range of application prospects. Radiometric correction converts the data recorded by sensors to ground reflectance and is the prerequisite for the quantitative application of UAV data. However, UAV data is susceptible to many factors such as illumination conditions, resulting in different degrees of radiometric differences between images, which makes it difficult for the radiometric correction of multiple UAV images. Based on the information of images' overlapping area, radiometric block adjustment can obtain the global optimal correction parameters, which has great potential in reducing the radiometric differences between the images and realizing the radiometric correction of images. But a large number of unknown parameters to be solved reduces the solution efficiency of the radiometric correction model, especially when the amount of data increases sharply, this problem will become more prominent. The optimal path established based on the radiometric information of images overlapping area takes into account the radiometric conversion relationship between the images, can effectively control the error accumulation, and provide an idea for reducing the number of unknowns in the radiometric block adjustment. Therefore, this paper combines the radiometric block adjustment with the optimal path to reduce the number of unknowns, and improve the calculation efficiency of the correction model while ensuring the accuracy of radiometric correction, thereby improving the application potential of the radiometric block adjustment on large datasets.

Key words: unmanned aerial vehicle, radiometric correction, optimal path, radiometric block adjustment

中图分类号:

P237

彭万山, 龚龑, 任杰, 周聪, 于亚娇. 基于最优路径的无人机影像辐射区域网平差[J]. 测绘通报, 2023, 0(1): 52-57,64.

PENG Wanshan, GONG Yan, REN Jie, ZHOU Cong, YU Yajiao. Optimal path-based radiometric block adjustment for unmanned aerial vehicle images[J]. Bulletin of Surveying and Mapping, 2023, 0(1): 52-57,64.

参考文献

[1] 李德仁, 李明. 无人机遥感系统的研究进展与应用前景[J]. 武汉大学学报(信息科学版), 2014, 39(5):505-513, 540.
[2] ZHOU Chengquan, YANG Guijun, LIANG Dong, et al. An integrated skeleton extraction and pruning method for spatial recognition of maize seedlings in MGV and UAV remote images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(8):4618-4632.
[3] 赵国帅. 无人机遥感在林业中的应用与需求分析[J]. 福建林业科技, 2017, 44(1):136-140.
[4] 王柯, 付怡然, 彭向阳, 等. 无人机低空遥感技术进展及典型行业应用综述[J]. 测绘通报, 2017(S1):79-83.
[5] 郭庆华, 胡天宇, 刘瑾, 等. 轻小型无人机遥感及其行业应用进展[J]. 地理科学进展, 2021, 40(9):1550-1569.
[6] LU Bing, He Yuhong. Species classification using unmanned aerial vehicle (UAV)-acquired high spatial-resolution imagery in a heterogeneous grassland[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 128:73-85.
[7] TEILLET P M. Image correction for radiometric effects in remote sensing[J]. International Journal of Remote Sensing, 1986, 7(12):1637-1651.
[8] MAFANYA M, TSELE P, BOTAI J O, et al. Radiometric calibration framework for ultra-high-resolution UAV-derived orthomosaics for large-scale mapping of invasive alien plants in semi-arid woodlands:Harrisia pomanensisas a case study[J]. International Journal of Remote Sensing, 2018, 39(15-16):5119-5140.
[9] SHIN J I, CHO Y M, LIM P C, et al. Relative radiometric calibration using Tie points and optimal path selection for UAV images[J]. Remote Sensing, 2020, 12(11):1726.
[10] 杨贵军, 万鹏, 于海洋, 等. 无人机多光谱影像辐射一致性自动校正[J]. 农业工程学报, 2015(9):147-153.
[11] CHANDELIER L, MARTINOTY G. A radiometric aerial triangulation for the equalization of digital aerial images and orthoimages[J]. Photogrammetric Engineering & Remote Sensing, 2009, 75(2):193-200.
[12] LI X H, HUI N, SHEN H F, et al. A robust mosaicking procedure for high spatial-resolution remote sensing images[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 109:108-125.
[13] 韩杰, 谢勇. 星载多相机拼接成像传感器在轨辐射定标方法[J]. 测绘学报, 2017, 46(11):1830-1840.
[14] HONKAVAARA E, SAARI H, KAIVOSOJA J, et al. Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture[J]. Remote Sensing, 2013, 5(10):5006-5039.
[15] 韩杰, 陶醉, 谢勇, 等. 顾及多积分时间特性的GF-4卫星PMS传感器交叉辐射定标[J]. 测绘学报, 2020, 49(10):1311-1320.
[16] PAN Jun, WANG Mi, LI Deren, et al. A network-based radiometric equalization approach for digital aerial orthoimages[J]. IEEE Geoscience and Remote Sensing Letters, 2010, 7(2):401-405.
[17] DENG Lei, HAO Xianglei, MAO Zhihui, et al. A subband radiometric calibration method for UAV-based multispectral remote sensing[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(8):2869-2880.
[18] HONKAVAARA E, HAKALA T, MARKELIN L, et al. A process for radiometric correction of UAV image blocks[J]. Photogrammetrie-Fernerkundung-Geoinformation, 2012, 2012(2):115-127.
[19] HONKAVAARA E, KHORAMSHAHI E. Radiometric correction of close-range spectral image blocks captured using an unmanned aerial vehicle with a radiometric block adjustment[J]. Remote Sensing, 2018, 10(2):256.
[20] XU Kaiqiu, GONG Yan, FANG Shenghui, et al. Radiometric calibration of UAV remote sensing image with spectral angle constraint[J]. Remote Sensing, 2019, 11(11):1291.