测绘学报 ›› 2022, Vol. 51 ›› Issue (9): 1951-1958.doi: 10.11947/j.AGCS.2022.20210023

• 摄影测量学与遥感 • 上一篇    下一篇

多波束与侧扫声呐图像的迭代自适应配准方法

章宁, 金绍华, 边刚, 肖付民   

  1. 海军大连舰艇学院军事海洋与测绘系, 辽宁 大连 116018
  • 收稿日期:2021-01-18 修回日期:2021-12-31 发布日期:2022-09-29
  • 通讯作者: 金绍华 E-mail:jsh_1978@163.com
  • 作者简介:章宁(1996—),男,硕士生,研究方向为多源数据融合与海底底质分类。E-mail:1845748146@qq.com
  • 基金资助:
    国家自然科学基金(41876103)

An iterative and adaptive registration method for multi-beam and side-scan sonar images

ZHANG Ning, JIN Shaohua, BIAN Gang, XIAO Fumin   

  1. Department of Military Oceanography and Hydrography and Cartography, Dalian Naval Academy, Dalian 116018, China
  • Received:2021-01-18 Revised:2021-12-31 Published:2022-09-29
  • Supported by:
    The National Natural Science Foundation of China(No. 41876103)

摘要: 针对目前多波束与侧扫声呐图像配准方法未顾及图像形变细节信息及二者尺度差异,存在局部纹理失真的问题,本文提出了结合小波变换、仿射变换和Demons配准算法的迭代自适应配准方法。利用小波变换提取侧扫声呐图像低频信息并重构图像,先后采用仿射变换和Demons算法将重构图像与多波束图像进行迭代自适应配准,获取配准变换模型,利用该模型对侧扫声呐原图像进行整体配准变换,获得多波束图像地理坐标约束的侧扫声呐图像。实例验证结果表明:该方法能有效实现多波束与侧扫声呐图像配准,获得位置准确且纹理丰富的融合声呐图像。

关键词: 多波束图像, 侧扫声呐图像, 图像配准, 小波变换, 仿射变换, Demons算法

Abstract: Aiming at the problem that the current multi-beam and side-scan sonar image registration methods fail to take into account the details of image deformation, the scale differences and exist local texture distortion, a iterative adaptive registration method combining wavelet transform, affine transform and Demons registration algorithm was proposed. By using wavelet transformation to extract the low frequency information from side scan sonar image and reconstruction images, using affine transformation and Demons algorithm to reconstruct image with iterative adaptive multi-beam image registration, obtain registration transformation model. The model is used to transform the original side-scan sonar image to obtain the side-scan sonar image constrained by the geographic coordinates of the multi-beam image. The results of example verification show that this method can effectively realize the registration of multi-beam and side-scan sonar images, and obtain the fusion sonar images with accurate position and rich texture.

Key words: multi-beam sonar image, side-scan sonar image, image registration, wavelet transformation, affine transformation, Demons algorithm

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