多波束与侧扫声呐图像的迭代自适应配准方法EI北大核心CSCD

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。

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

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.