测绘通报 ›› 2019, Vol. 0 ›› Issue (7): 147-150.doi: 10.13474/j.cnki.11-2246.2019.0237

• 夜光遥感技术及应用 • 上一篇    下一篇

去除DMSP/OLS影像模糊的RTSVD算法

于志文1, 任超1,2, 邓开元1, 毕旋旋1   

  1. 1. 桂林理工大学测绘地理信息学院, 广西 桂林 541004;
    2. 广西空间信息与测绘重点实验室, 广西 桂林 541004
  • 收稿日期:2018-11-23 修回日期:2019-01-11 出版日期:2019-07-25 发布日期:2019-07-31
  • 通讯作者: 任超。E-mail:renchao@glut.edu.cn E-mail:renchao@glut.edu.cn
  • 作者简介:于志文(1995-),女,硕士生,主要研究方向为遥感数据处理及空间数据挖掘。E-mail:yzw8111@163.com
  • 基金资助:
    国家自然科学基金(41461089);2018年度广西高校中青年教师基础能力提升项目(2018KY0247);广西空间信息与测绘重点实验室项目(16-380-25-22;15-140-07-34)

RTSVD algorithm to remove DMSP/OLS image blurring

YU Zhiwen1, REN Chao1,2, DENG Kaiyuan1, BI Xuanxuan1   

  1. 1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
    2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China
  • Received:2018-11-23 Revised:2019-01-11 Online:2019-07-25 Published:2019-07-31

摘要: DMSP/OLS作为最早的夜光遥感数据具有很大的应用价值,解决该数据存在的模糊问题,能够大幅提高数据质量。本文分析模糊原因,提出了一种结合Pct影像发光频率滤波的正则化截断奇异值分解(RTSVD)算法,该算法能有效消除影像模糊现象并保留影像真实信息。首先考虑到光源像素发光频率必定高于非光源像素,利用Pct影像中的像素发光频率排除平均灯光影像中的非光源像素,然后利用L曲线求得正则化截断奇异值分解的截断参数,以此对影像进行分解重组。试验表明,结合Pct影像发光频率滤波的正则化截断奇异值分解法可在保留影像信息的基础上去除模糊现象。

关键词: 夜光遥感, 去模糊, 正则化, 截断奇异值分解, L曲线

Abstract: DMSP/OLS, as the earliest nighttime light remote sensing data, has great application value and can greatly improve the data quality by solving the blurring problem existing in the data. The blur reason is analyzed, and a new algorithm of regularization truncated singular value decomposition (RTSVD) combining with Pct image luminescence frequency filtering is proposed, which can effectively eliminate the blurring phenomenon and retain the real information of the image. Firstly, considering that the luminescence frequency of the light source pixel must be higher than that of the non-light source pixel, the luminescence frequency of the pixel in the Pct image is used to exclude the non-light source pixel in the average light image, and then the truncation parameter of the regularized truncation singular value decomposition (RTSVD) is obtained by using the L curve, so as to decompose and recombine the image. The experiments show that the regularized truncation singular value decomposition method combined with Pct image luminescence frequency filtering can remove the blurring phenomenon on the basis of preserving the image information.

Key words: nighttime light, deblurring, regularized, TSVD, L-curve

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