基于SPHP的推扫式高光谱航空影像拼接
投稿时间:2020-01-17  修订日期:2021-01-12  点此下载全文
引用本文:李赛,尹球,胡勇,巩彩兰.基于SPHP的推扫式高光谱航空影像拼接[J].红外与毫米波学报,2021,40(1):64~73].LI Sai,Yin Qiu,HU Yong,GONG Cai-Lan.A push-sweep hyperspectral aerial image Mosaic method based on SPHP[J].J.Infrared Millim.Waves,2021,40(1):64~73.]
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作者单位E-mail
李赛 中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083
中国科学院大学北京 100049 
814100090@qq.com 
尹球 上海市气象局上海 200030  
胡勇 中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083 
 
巩彩兰 中国科学院上海技术物理研究所上海 200083
中国科学院红外探测与成像技术重点实验室上海 200083 
 
基金项目:高分辨率地球观测系统重大专项青年创新基金项目(编号:GFZX04061502);上海市水务局科研项目(2018-07)
中文摘要:针对高光谱推扫影像间相机光心不重合,在配准过程中利用传统全局单应性矩阵对齐方式会有误差的问题,提出了一种基于SPHP(Shape-Preserving Half-Projective)并且考虑光谱信息的高光谱推扫图像的拼接方法(H-SPHP)。主要步骤包括:1)基于正解法的视矢量几何校正;2)基于先验知识和PCA的基准波段选择;3)基于SPHP的网格优化对齐方法;4)加权平均融合算法进行融合;5)将拼接参数应用于所有波段,得到拼接后的高光谱数据。对福建三明和江西南昌等区域获取实验影像,通过对研究数据的拼接实验表明,本文算法具有很强的鲁棒性,消除视差和地理坐标精度比SIFT+单应性变换算法都有较大提高,拼接后波段间配准精度在一个像元内,重叠区光谱相似度在90%以上。
中文关键词:航空摄影测量  影像拼接  H-SPHP  高光谱推扫影像
 
A push-sweep hyperspectral aerial image Mosaic method based on SPHP
Abstract:In order to solve the problem that the optical center of hyperspectral images does not coincide with each other, and the alignment of traditional global monotonic matrix may have error in the registration process, a splicing-method (H-SPHP) of hyperspectral images based on SPHP(shape-preserving half-projective) and considering spectral information is proposed. The main steps include as follows: 1) image correction using the visual vector method. 2) selection of reference band based on prior knowledge and PCA. 3) SPHP-based mesh optimization splicing method. 4) Weighted average fusion algorithm for fusion.5) splicing parameters applied to all bands to obtain the splicing hyperspectral data. By obtaining experimental images from Sanming, Fujian province and Nanchang,Jiangxi province, the research data splicing experimental results show that the proposed algorithm has strong robustness, eliminating parallax and geographic coordinates accuracy better than SIFT + single should transform algorithm. After splicing, the registration accuracy of bands is within one pixel, and spectral similarity of the overlapping region is above 90%.
keywords:aerial photogrammetry  image mosaic  H-SPHP  hyperspectral push-scan image
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