基于极坐标Lagrange插值的航拍图像畸变校正算法

马天娇; 韩广良; 孙海江

doi:10.3788/YJYXS20183305.0418

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基于极坐标Lagrange插值的航拍图像畸变校正算法

图像处理 | 更新时间：2020-08-12

- 基于极坐标Lagrange插值的航拍图像畸变校正算法
- Aerial image distortion correction algorithm based on polar coordinate Lagrange interpolation
- 液晶与显示 2018年33卷第5期页码：418-426
- 作者机构：
  
  1.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2.中国科学院大学, 北京 100049
- 作者简介：
  
  韩广良, E-mail: hangl@ciomp.ac.cn
- 基金信息：
- DOI：10.3788/YJYXS20183305.0418
  中图分类号： TP391.4
- 收稿日期：2017-12-16，
  
  录用日期：2018-2-28，
  
  纸质出版日期：2018-05
- 稿件说明：
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马天娇, 韩广良, 孙海江. 基于极坐标Lagrange插值的航拍图像畸变校正算法[J]. 液晶与显示, 2018,33(5):418-426.

Tian-jiao MA, Guang-liang HAN, Hai-jiang SUN. Aerial image distortion correction algorithm based on polar coordinate Lagrange interpolation[J]. Chinese journal of liquid crystals and displays, 2018, 33(5): 418-426.
马天娇, 韩广良, 孙海江. 基于极坐标Lagrange插值的航拍图像畸变校正算法[J]. 液晶与显示, 2018,33(5):418-426. DOI： 10.3788/YJYXS20183305.0418.

Tian-jiao MA, Guang-liang HAN, Hai-jiang SUN. Aerial image distortion correction algorithm based on polar coordinate Lagrange interpolation[J]. Chinese journal of liquid crystals and displays, 2018, 33(5): 418-426. DOI： 10.3788/YJYXS20183305.0418.

摘要

由于航拍图像的拍摄高度远低于卫星图像拍摄高度，因此每个拍摄地点的建筑投影差大小和方向都不相同，图片畸变严重。此外，考虑到图像边缘区域的畸变程度远大于图像中心区域的畸变程度，本文提出了一种基于极坐标的Lagrange插值的逐点畸变校正方法。利用该方法在极坐标系内对单个像素点进行插值，然后根据插值结果对像素点进行校正，再将其坐标从极坐标系变换回直角坐标系，最后采用此方法在整个航拍图像内逐点进行畸变校正。实验结果表明，校正后的航拍图像畸变程度不超过3%，证明该方法不但能有效地校正畸变图像，且与传统的利用DLT线性求解畸变校正矩阵等校正方法相比具有更为广泛的适用性。

Abstract

Since the height of aerial image shot is much lower than the height of satellite image shot

this may lead to the differences of the projection sizes and directions between every shooting location

which will result in serious picture distortion in most cases. In addition

the degree of distortion of the image edge region is much more serious than that in the center region

a distortion correction method based on Lagrange interpolation of polar coordinates has been proposed by this paper. We use this method to interpolate the single pixel in polar coordinates system. The pixel coordinate expression will be reconverted from polar coordinates to Cartesian coordinates after we corrected the pixel according the consequence of interpolation. And finally this method will be used to correct distortion pixel-by-pixel throughout the aerial image. The experiment results show that the corrected aerial image distortion does not exceed 3%

which proves that this algorithm can not only correct distortion image effectively

but also has a wide applicability compared with the traditional distortion correction methods

such as making use of the Direct Linear Transformation to obtain the distortion matrix.

关键词

Keywords

references

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