测绘通报 ›› 2023, Vol. 0 ›› Issue (4): 154-158.doi: 10.13474/j.cnki.11-2246.2023.0121

• 技术交流 • 上一篇    下一篇

基于频谱融合的近景摄影影像灰度质量分析

张辰1, 吴兆福1, 黄建伟1, 余敏1, 王璐1, 李水平2   

  1. 1. 合肥工业大学, 安徽 合肥 230009;
    2. 武汉引力与固体潮国家野外科学观测研究站, 湖北 武汉 430075
  • 收稿日期:2022-04-14 发布日期:2023-04-25
  • 通讯作者: 余敏。E-mail:yumin@hfut.edu.cn
  • 作者简介:张辰(1998—),男,硕士,主要从事近景摄影测量研究工作。E-mail:1603137351@qq.com
  • 基金资助:
    武汉引力与固体潮国家野外观测研究站开放基金(WHYWZ202107);中央高校基本科研业务费专项资金(JZ2020HGQA0139)

Quality analysis on the image greyscale for the close-range photogrammetry based on the spectrum fusion method

ZAHNG Chen1, WU Zhaofu1, HUANG Jianwei1, YU Min1, WANG Lu1, LI Shuiping2   

  1. 1. Hefei University of Technology, Hefei 230009, China;
    2. National Observation and Research Station of Wuhan Gravitation and Solid Earth Tides, Wuhan 430075, China
  • Received:2022-04-14 Published:2023-04-25

摘要: 近景摄影测量已被广泛应用于基坑监测、工业测量、文物修复等领域。在长时序近景摄影测量监测中,图像灰度变化对监测精度的影响仍是需要解决的问题。本文以合肥轨道交通5号线2标段扬子江车站基坑监测为工程背景进行研究。首先分析影像灰度变化对监测精度的影响,确定最优灰度区间;然后采用频谱融合法对非最优灰度区间影像灰度进行改正,将影像原有相位谱与最优灰度影像的幅度谱进行融合,调节灰度至最优灰度区间,并进行精度分析。试验结果表明:精度最高时对应的影像最优灰度范围为139.0~173.8;频谱融合处理后影像精度提升了43.7%~79.5%,变异系数降低,数据稳定性提高。研究结果为长时序近景摄影测量中由灰度原因引起的影像精度不佳问题提供了一种新的解决思路。

关键词: 近景摄影测量, 长时序监测, 影像灰度, 最优灰度区间, 频谱融合

Abstract: Close-range photogrammetry has been widely used in foundation pit monitoring, industrial surveying, cultural relic restoration and other fields. The monitoring accuracy affected by the image greyscale variation remains the solving problem during the long-term close-range photogrammetry. In this paper, the foundation pit monitoring of Yangzijiang River station in Section 2 of Hefei rail transit Line 5 is selected as the engineering background. Firstly, the influence of image grayscale variation on the monitoring accuracy is analyzed. And the optimal grayscale interval is determined. Then, the spectral fusion method is used for the greyscale correcting on the image with non-optimal greyscale interval. The original phase spectrum of the image is fused with the spectrum with optimal greyscale image, leading to the adjustment to the optimal greyscale interval. The matching accuracy before and after the spectrum fusion is analyzed. The experimental results show that the optimal greyscale range of the image of the highest accuracy is 139.0~173.8. After spectrum fusion, the image accuracy is improved on 43.7% to 79.5%. The reduced variation coefficient can lead to the improved data stability. This paper can provide a new solution to the problem of poor image accuracy caused by greyscale variation of long-term close-range photogrammetry.

Key words: close-range photogrammetry, long time series monitoring, image greyscale, optimal grayscale interval, spectrum fusion

中图分类号: