Sonar images are valuable in exploring underwater environmental information. As these images are generally limited by the viewing angle, sonar image mosaicking becomes an important research topic. By combining several frames consecutively acquired while the underwater vehicle is manoeuvring, an image with a wider view can be obtained. This study presents a fast sonar image mosaicking approach consisting of denoising, feature extraction, initial matching, splicing, and optimisation. Based on the Euclidean distance between initially matched points and dip angle of connection line, poorly matched feature point pairs are removed to avoid false matching. This way, the success rate of image mosaicking and quality of the resulting mosaicking is effectively improved.

中文翻译：

---

基于新特征匹配方法的声纳图像拼接

声纳图像对于探索水下环境信息非常有价值。由于这些图像通常受到视角的限制，因此声纳图像镶嵌成为重要的研究课题。通过组合在操纵水下航行器时连续获取的几个帧，可以获得具有较宽视野的图像。这项研究提出了一种快速的声纳图像镶嵌方法，包括降噪，特征提取，初始匹配，剪接和优化。根据初始匹配点之间的欧几里得距离和连接线的倾角，可以消除匹配不佳的特征点对，从而避免错误匹配。这样，有效地提高了图像镶嵌的成功率和所产生的镶嵌的质量。